Penguin Random House

Author of the instant New York Times Bestseller, The 5 Types of Wealth: A Transformative Guide to Design Your Dream Life.

Author

The Curiosity Chronicle

The Curiosity Chronicle is a 4x weekly newsletter where I provide actionable ideas to help build a high-performing, healthy, wealthy life to a global community of 800,000+.

Writer

SRB Holdings

SRB Holdings is a personal holding company currently comprised of ten cash flowing business assets.

Current portfolio holdings include:

• SBloom Media Holdings
• The Inflection
• Paperboy Studios
• SBloom Advisory

Owner

SRB Ventures

SRB Ventures is an investment firm committed to investing in and accelerating the most compelling startups in the world. Fund I is a $10 million stage and sector-agnostic vehicle writing $100-250K checks into high-growth technology companies around the world.

Managing Partner

NYT Bestselling Author of The 5 Types of Wealth

Sahil Bloom is the New York Times Bestselling author of The 5 Types of Wealth: A Transformative Guide to Design Your Dream Life.

Sahil is an inspirational writer and entrepreneur, captivating millions of people every week through his book, social insights, and bi-weekly newsletter, The Curiosity Chronicle.

His debut non-fiction book, The 5 Types of Wealth, was an instant New York Times, USA Today, and Sunday Times Bestseller. Apple CEO Tim Cook called it "a powerful call to action to think deeply about what lights you up—and a guide for how to build a life of meaning and purpose around those things." The book is a unique blend of strategies, tactics, and actionable insights, enabling readers to make real, positive changes and lead healthier, wealthier lives.

Sahil is also an entrepreneur and owner of SRB Holdings, a personal holding company, and the Managing Partner of SRB Ventures, a $10 million venture investment firm committed to investing in and accelerating the most compelling startups in the world. Prior to launching SRB Ventures in January 2022, Sahil was an early-stage investor in 40+ startups across the technology landscape, including multiple unicorns.

Previously, Sahil spent seven years as a private equity investor and served on the board of several middle market companies during that period.

Sahil graduated from Stanford University with an M.A. in Public Policy (2014) and a B.A. in Economics & Sociology (2013). While at Stanford, he was a four-year member on the Stanford Baseball Team (2009-2013), twice helping to guide the team to NCAA Super Regional appearances (top-16 finishes). Additionally, Sahil earned two PAC-12 All-Academic Team awards and twice received the Bruce R. Cameron Memorial Award, given annually to a student-athlete exhibiting excellence in athletics, academics, and leadership. Academically, Sahil was advised in his pursuits by former Secretary of State Dr. Condoleezza Rice.

Sahil Bloom

This letter stopped me in my tracks…

Every single person you meet is fighting a battle you know nothing about.

Your one tiny action can create ripples that extend far beyond yourself.

Create more ripples.

For anyone out there battling in silence, you’re not alone.

We’re all in it together.

Lift someone up this week for no reason at all.

“I hope you win the war you tell no one about.”

Enjoy this? Share it with your network and follow me Sahil Bloom for more.

P.S. I write about these topics in my 4x weekly newsletter. Join 800,000+ other readers (completely free): https://lnkd.in/esGsF85Q

This poem changed my life

(and may change yours):

“It is said that before entering the sea
a river trembles with fear.

She looks back at the path she has traveled,
from the peaks of the mountains,
the long winding road crossing forests and villages.

And in front of her,
she sees an ocean so vast,
that to enter
there seems nothing more than to disappear forever.

But there is no other way.
The river can not go back.

Nobody can go back.
To go back is impossible in existence.

The river needs to take the risk
of entering the ocean
because only then will fear disappear,
because that's where the river will know
it's not about disappearing into the ocean,
but of becoming the ocean.”

– Khalil Gibran

Reading (and re-reading) the poem sparked four powerful thoughts:

1. Fear is natural before transformation. That fear you feel as you approach a significant change is completely natural. It’s a cost of entry for the transformation you wanted.

2. There is no going back. On your growth journey, there is no turning back. A few weeks ago, ​I wrote​, “I believe that the worst mistakes in life are made when we try to cling to a prior season that has already passed.” We cannot undo experiences or retreat into old versions of ourselves. Always forward.

3. Surrender is necessary for growth. The attachment to a present identity (“the river”) holds you back from your true potential. To become the new, you have to unbecome the old. You have to let go of your old habits, mindsets, beliefs, and identity. That requires a leap of faith. That requires a surrender.

4. It’s not a loss, it’s an expansion. What feels like a loss or disappearance of the old is often just an expansion into the richness of the new. The river does not disappear into the ocean, it becomes the ocean.

The river’s story is our story.

So, what ocean are you afraid to enter?

Maybe it’s time you surrendered to it.

And when you do, remember this:

You are not disappearing, you are becoming.

📌 Want the books that built my best systems and ideas?

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The highest form of intelligence isn’t IQ.

(this realization changed my life)...

It’s adaptability.

Knowledge matters, but the ability to learn, unlearn, and change course matters more. The rigid cling to what was. The adaptable adjust to what is and what will be.

The future belongs to them.

♻️ Enjoy this? Repost to share with your network!

And follow Sahil Bloom for more!

The brutal truth about confident people?

(they fail more than you do)...

Confidence is less about knowing you’ll win and more about knowing you’ll bounce back even if you don’t.

Real confidence is built on resilience. Adaptability. Tolerance for uncertainty.

Fear loses when you embrace that failure is never final.

📌 Want wisdom that helps you focus on what truly matters?

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The most attractive trait…

(it’s not looks, wealth or status).

It’s energy.

Walk into rooms with genuine enthusiasm, curiosity, and interest. You’ll become a magnet for the highest quality people.

Energy is contagious. Spread the kind you’d want to catch.

📌 Want the morning/evening routine that built my most productive days?

Download my Morning/Evening Routines PDF (free) and join 800,000+ who get my newsletter: https://lnkd.in/eehamdDj

The #1 predictor of success isn't talent.

(most people never figure this out)...

It’s reliability. 

You’ll achieve much more by being consistently reliable than by being occasionally extraordinary. Show up, do the work, repeat. 

The recipe for success in any area of life.

📌 Want the morning/evening routine that built my most productive days?

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The smartest people I know aren't the most knowledgeable.

(they have something else entirely)...

They adapt faster than everyone else.

I spent my 20s collecting credentials. MBA. Finance roles. The "right" path. I thought intelligence meant having all the answers.

Then markets crashed. Industries transformed. Everything I "knew" became obsolete overnight.

That's when I learned: The rigid cling to what was. The adaptable adjust to what is and what will be.

Your expertise? A liability if you're too attached to it.

Your identity? A prison if it prevents you from evolving.

The future belongs to those who rewrite the manual when the game changes.

Every time you say "that's not how we do things," you're choosing rigidity over intelligence.

Adaptability isn't just surviving change—it's thriving because of it.

📌 Ready to invest in yourself?

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This idea completely changed my life…

The Snake Chasing Effect:

A man is walking through the woods when he stumbles across a snake in the center of his path. The snake lashes out and bites him without warning, then turns and slithers away down the path. The man feels the sharp pain of the bite and the venom coursing through his leg. Fortunately, he's close to the village, so if he just walks back and gets the wound treated, he'll be fine. But he feels the anger and resentment building inside him: "Why did the snake do that to me? That's not right. I'm going to get revenge."

He starts chasing down the snake path, but as he pursues the snake, the venom takes hold and he collapses and dies. The story offers a powerful lesson, which you might call the Snake Chasing Effect: In life, you're going to get bitten by a snake every now and then. Someone betrays you. A partner lies. A family member mistreats you. A friend lets you down. A coworker takes credit for your work. The initial wound hurts—but it's survivable. If you take care of yourself, walk back to the village and treat the wound, you'll be fine.

But how often do you do the exact opposite? The internal voice starts a familiar refrain: How could they do this to me? I'm going to get them back. You start chasing the snake down the path, seeking your revenge. You obsess over the betrayal. The unfairness. The injustice. The real damage is not from the bite itself, but from your reaction to it. The real damage comes when you chase the snake.

The Snake Chasing Effect is a reminder that the wisest response to harm isn't retaliation or obsession, but restoration. Don't give the snake more power of you than it has. Focus on healing, not hunting. Tend your wound. Mend your garden. Your rebirth is the greatest revenge.

📌 Want frameworks that evolve with you, not confine you?

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The Snake Chasing Effect

One thing predicts where you'll be in 10 years…

(and it's completely in your control).

Your standards.

Every time you let something slide “just this once”, you train yourself to accept less.

That’s how goals erode. That’s how principles slip.

Set your standards. Hold the line. Especially when it’s hard.

📌 Want the morning/evening routine that built my most productive days?

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This poem stopped me cold.

(you need to read this):

"In this short Life
That only lasts an hour
How much - how little - is
Within our power"

- Emily Dickinson

Four lines. Still hitting harder than any productivity guru's 300-page book.

Here's what Dickinson understood that we miss: 

Life isn't just short—it's embarrassingly short. Even when you intellectually know this, you still waste Tuesday afternoons scrolling. You still put off the hard conversation. You still wait for "someday."

But hidden in those lines is the real wisdom: "How much - how little."

It's both. Always both.

You have more power than you think—to change careers, repair relationships, build something meaningful. But you have less power than you assume—over outcomes, other people's choices, the speed of change.

The magic happens when you accept both truths.

Stop trying to control what was never yours to control. Stop giving away power over what IS yours to command.

Your thoughts. Your effort. Your next decision. That's your kingdom. Everything else? Let it go.

Life is shorter and more fragile than you realize. But within your small sphere of control, you're more powerful than you've ever imagined.

The question isn't whether life is short. The question is: What are you doing with the power you actually have?

📌 Want wisdom that helps you focus on what truly matters?

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The hardest lesson I learned about success…

(it came from a farmer):

A farmer doesn't dig up his seeds every day to make sure they're growing.

He plants, waters, and waits. You can't rush what needs time to take root. Growth hides beneath the surface long before it's visible above it.

Remember that.

📌 Want the morning/evening routine that built my most productive days?

Download my Morning/Evening Routines PDF (free) and join 800,000+ who get my newsletter: https://lnkd.in/eehamdDj

The #1 struggle nobody admits to…

(especially high performers):

Eliminating the guilt associated with free time and rest.

📌 Want the morning/evening routine that built my most productive days?

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How to win in life…

(without talent or luck):

Operate in Your Zone of Genius
Your Zone of Genius is where your interests, passions and skills align.

Adopt a Positive Sum Mentality
Want to get ahead in life? Start genuinely rooting for others to succeed.

Speak Up
A little push goes a long way. Don't sit back and wait for good things to happen.

Play Long-Term Games
In a world of people seeking instant gratification, this is a meaningful edge.

Have a High Tolerance for Failure
We fear failure, so most of us play it safe to avoid it.

Follow Your Curiosity
For the curious mind, anything is possible. Fortune favors the curious.

Adopt a Process Orientation
Prioritize process, not outcomes.

Prioritize People
Everything in life comes down to people and relationships.

Work Like a Lion
If your goal is to do inspired, creative work, you have to work as a lion works.

Become Antifragle
Don't be broken by the chaos—rather, adopt a mentality and build structure such that you will benefit from it.

Change Your Mind
It's great to have a strong view, but always open your mind to counterarguments.

Never Get Too Big to Do the Small
Whether you're in the mailroom or the corner office, never get too big to do the small things well.

Learn Storytelling
High-leverage storytelling is a supercharger for all human endeavors.

Develop a Bias for Motion
A body in motion tends to stay in motion—a body at rest tends to stay at rest.

Become Relentlessly Consistent
Many people are able to produce bursts of energy—few are able to produce consistent, steady flows of energy.

Simplify Where Others Complicate
Learn to convey the complex in simple, digestible ways.

Be Comfortable with Discomfort
Discomfort is a precursor to growth—it is an absolute necessity.

Have Strong Plans (Loosely Held)
Plans have to be dynamic (and punch-proof!).

Pay It Forward
Pay it forward. Be a mentor. Be a champion for others.

Well there you have it—How to Win (without talent or luck).

Use them to earn trust.
Use them to build leverage.
Use them to win your game.
Start small. Stay consistent.

And remember: You already have everything you need.

📌 Want the decision-making razors that power my best choices?

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How To Win (without talent or luck)

Amateur vs. Pro

(11 signs you're still an amateur):

1. Amateurs let the day come to them, Professionals have a routine
The greatest performers in any craft share one trait in common: They have a routine—and they stick to it with intense discipline.

2. Amateurs love the prize, Professionals love the process
You’ll never make it if the view at the summit is the only thing motivating you to keep climbing.

3. Amateurs make it look effortful, Professionals make it look effortless
The Paradox of Effort: You have to put in more effort to make something appear effortless.

4. Amateurs blame others, Professionals are accountable
In the wake of a failure, there are two types of responses:
The Amateur looks outward—bad luck, unfair circumstances, a cheating opponent.
The Professional looks inward—lack of preparation, gaps in routine, uneven intensity.

5. Amateurs are flashy, Professionals are relentless
Many people are able to produce bursts of energy—few are able to produce consistent, steady flows, day in, day out.

6. Amateurs enter with 100 mediocre moves, Professionals enter with 1 perfect move
Professionals identify their unique edge—they play their game.

7. Amateurs fear failure, Professionals embrace it
The Paradox of Failure: The more you fail, the more you ultimately succeed.

8. Amateurs fear being wrong, Professionals enjoy it
When faced with their own incompetence:
The Amateur flails wildly in an attempt to distract from the obvious gap.
The Professional enlists support to cover the incompetence and repositions the board to avoid its exposure.

9. Amateurs are impatient, Professionals are patient
Amateurs are: Patient with actions and impatient with results.
Professionals are: Impatient with actions and patient with results.

10. Amateurs hope for good breaks, Professionals create them
Amateurs enter the arena with their fingers crossed.
Professionals enter the arena with a plan.

11. Amateurs press, Professionals wait
When pressure and stress levels elevate:
The Amateur is uncomfortable—they press in an effort to fast-forward to the finish.
The Professional is comfortable—they observe their opponent and wait for the opportune moment to strike.

📌 Want frameworks that evolve with you, not confine you?

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Amateur vs Pro - 11 Differences

This study blew my mind…

(you need to read this):

The Harvard Study of Adult Development is the longest running study on happiness.

Here are 3 powerful findings everyone should know:

1. Relationship satisfaction impacts health.

The researchers looked back at the lives of the 80-year-old participants to determine what factors were predictive of healthy aging.

What did they find?

Relationship satisfaction at age 50 was predictive of health at age 80.

Study director Robert Waldinger:

"It wasn't their cholesterol levels that predicted how they were going to grow old. It was how satisfied they were in their relationships. The people who were the most satisfied in their relationships at age 50 were the healthiest at age 80."

2. Loneliness kills.

Humans are social creatures. We thrive through connection to those around us.

Study participants who felt isolated were observably less happy and experienced notably earlier declines in health than those who felt connected.

The study observed the negative impacts of alcohol and smoking on the long-term health of the participants, but found that loneliness was just as negatively impactful.

Study director Robert Waldinger:

"Loneliness kills. It's as powerful as smoking or alcoholism."

3. Quality over quantity.

The researchers found that the quality of relationships was more impactful on health and happiness than the quantity of relationships.

A few deep bonds are worth far more than hundreds of weak or unhealthy ones.

Relationships are, quite literally, everything.

Hopefully the insights from my conversation with Dr. Robert Waldinger shine a light on their importance—and hopefully you take a few tiny actions that improve your Social Fitness in the days and weeks ahead.

Invest in your relationships—they will pay dividends in all areas of your life for many years to come.

📌 Want the decision-making razors that power my best choices?

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The Longest Running Study on Happiness

How to get your dream life…

(the truth nobody wants to hear):

I used to stare at closed doors. The dream job. The meaningful relationship. The healthy body.

I'd tell myself they were "locked" for people like me.

Then I learned the truth: Every door has a key. You just have to pay the cost of entry.

Freedom requires focus. You can't have it all, so you must choose what matters.

Deep bonds demand vulnerability. No armor allowed. Just your real, messy self.

Health needs discipline. Every single day. Especially when you don't feel like it.

Here's what nobody tells you: 

The cost is always higher than you think. But the reward? It's always worth more than you imagined.

Most people window shop their dreams. They want the outcome without the entry fee.

That promotion? It costs uncomfortable conversations.

That relationship? It costs emotional risk.

That transformation? It costs your old identity.

Pay the price or stay outside. There's no third option.

That's why 800,000+ readers trust my newsletter to help them unlock what matters.

Four times a week, I share:

• Frameworks to identify what's worth the cost
• Systems to pay the price consistently
• Tools to unlock doors faster
• Insights that make the journey worthwhile

Because every lesson I wish I knew earlier starts the same way: Embrace the cost of entry with pride.

The doors you want are waiting. Time to pay up.

📌 Ready to invest in yourself?

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Adway

- 39 ATS analysis & reporting to clients; improving renewal success by 70%
- Automated monthly sales reports with Python, saving 15 hours per month. 
- On our way to 100M ARR in 2025, leveraging data and tech.
- Tech stack: M365, Excel, Python, PowerPoint, Loom

Data Scientist & BI Consultant

Alterfy

Advising the software and data team in building a robust SaaS web app leveraging AI,  analytics, and data. Perform data analyst and data scientist tasks by measuring KPIs and building machine learning models.

AI & Tech Advisor

ROCK

- Led the BI using tools like BrightGauge, PowerBI, and HaloPSA to create and update over 200 reports and dashboards.
- Managed the data transition for an MSP used internally called HaloPSA which delivers a 5x growth to the company.
- Data engineering, and data science work on Microsoft Fabric (pipelines, Lakehouses, Warehouses, Notebooks...)
- Data consulting in data projects for clients.

Data Scientist

Kadogoodiz

Head of data science and analysis with the goal of fetching, cleaning, analyzing, and reporting data to senior partners.

Uhubs

+ Analyzing the data sets to extract insightful information (Python, Pandas).
+ Cleaning and feature engineering on data sets.
+ Integrated natural language processing (NLP) to analyze textual data (nltk, stemming, tokenizing).
+ Visualized insightful information (Matplotlib, Seaborn, Plotly)
+ Deep research on benchmarking to increase sales workflow.
+ visualizations and reporting

Consultant Data scientist

Riad coaching

Performance Coach

Setexam – The Agar Specialists

+ Maintained databases using MySQL
+ Handled part of the AWS infrastructure and migration from on-premises to the cloud
+ Cleaned data prior to training and analysis using Python (Pandas, NumPy)
+ Visualized important metrics and outputs using Matplotlib and Seaborn
+ Been part of the machine learning team and made sure to apply best practices and optimize the code.

Assistant data scientist

+ Designed maintenance software ‘Coswin 7’ and trained technical staff to use it for preventive and corrective maintenance.
+ Trained a newly hired maintenance technician to manage and use Coswin 7 for troubleshooting and effective use.
+ Automated part of the process concerning the dosing and transfer of chemicals for cleaning purposes using Allen Bradley API language.
+ Supervised and visualized in real-time the automated process via RSLogix 500.
+ Worked with IO-Link, a modern technology of sensor/actuator that was added to the company’s workflow.

Engineer Intern

Syndic8

Collective created with a bunch of friends in 2015, eager to grow the Moroccan musical scene. 
As a co-founder and musician I dealt with :

+ 10+ High-quality events all over Morocco
+ Booking 16 International renowned artists. 
+ Budgets ranging from 1000-13500£.
+ Communication over Facebook and Instagram + Ads
+ Performing live as a professional around Morocco and France

Co-Founder

+ Exploring the industrial world, API's, sensors, programs, servers, machines, supervision, maintenance...

Stagiaire en ingénierie industrielle

🤖Data Scientist | Turning Raw Data into Money Generating Insights | Data-led Growth for Your Business 🚀

Freelance Data Scientist | ML Engineer | SQL | Python | Power BI | MLOps

Data analytics and Machine learning models built 5X faster - no quality compromise. Worked with 14 clients in 7 different industries in the last 3 years. Helped current company scale to $5M+ ARR. Featured TOP RATED PLUS talent on Upwork in 2025 with 100% job completion and satisfaction.

My Toolkit:
- Data analytics: Python, SQL, Excel
- ML Engineering: FastAPI, AWS, Streamlit, great_expectations
- Data visualization: PowerPoint, PowerBI, Plotly, Matplotlib
- Data modeling: Scikit-learn, TensorFlow, Keras
- MLOPs: CI/CD (GitHub Actions), Docker
- Additional tools: Notion, n8n, Canva, Git/GitHub

My Stats:
- 5-stars reviews on 99% of projects delivered.
- 100% Job Success Score for on-time, budget delivery.
- Helped scale currently business to $5M ARR with ATS analysis & Reporting.
- 1 year TOP RATER PLUS on Upwork.
- 1200 hours billed.
- $40k+ earned.

What You’ll Get Working With Me:
- A data analyst who is a real problem solver.
- Quick responses (within the hour on working hours)
- Clean, maintainable code and detailed documentation
- A clear “NO” if something isn’t feasible; no wasted time
- A well-crafted report or dashboard as per the requirements

My clients think:
- "Anas is great and highly knowledgeable. He is passionate about solving data science challenges and has helped me significantly streamline some of my processes, enabling better scalability.
- "Anas, was prompt and thorough and I would def use him again in the future."
- "Anas is great to work with. He made the job so fluid and his knowledge of data science makes him someone worth listening to. I’m glad I chose him for my small business. I’m looking forward to what’s coming next, and I would definitely hire him again."

Popular Clients & Products:
- Uhubs: Financial company based in London
- AllAboutGroup: Law recruitment firm based in London
- Growth Dynamics: Marketing and data strategist based in London.
- Adway: Tech and recruitment company based in Gotheborg, Sweden

About me:
- Football fan since I can remember (Real Madrid fan)
- Tennis lover and practitioner (one-handed backhand style)
- Mangas fan (One Piece, Naruto, Bleach)
- Travel addict (South Asia, Europe, Africa, America (soon))
- Reading is something I enjoy as much as coffee (oat latte fan recently)

-----

YouTube Channel
→ GO HERE: https://www.youtube.com/anas_riad

Request services via LinkedIn or Email below:
r.riadanas@gmail.com

Anas Riad

The ML project you wish you built sooner.
2.5hr of hands-on learning ⤵️

No excuses for skipping end-to-end ML now! 🤣

(PS: Link to the full YT video in the comments)

When I first started working on churn prediction, 
I noticed something that always bothered me.

There are tons of Regression projects out there, 
but 𝟗𝟗% 𝐨𝐟 𝐭𝐡𝐞𝐦 stop at the notebook.

It’s like drawing the blueprint for a house but never building it.

So I created a full end-to-end regression project that goes from:
raw dataset → trained model → deployment → tests → cloud.

Here’s what I cover in this project & video:
→ Split data by date (time-series aware)
→ Data Quality with Great Expectations
→ Well-structured pipelines (feature, training & inference)
→ Unit & smoke tests to keep things reliable
→ Experiment tracking with MLflow
→ Containerization with Docker
→ FastAPI serving layer
→ CI/CD with GitHub Actions
→ AWS (ECS, ECR, S3, ALB) for Deployment

It’s the same type of stack I use in freelance + personal work, but applied to regression.

Looking forward to your thoughts on it.

🌟 Link to the full YT video in the comments

PS: Would you be interested in a dedicated hands-on MLE platform? 🤔

Data Scientist & BI Consultant @Adway • ML Engineer • YouTube @ Anas Riad

The ML project you wish you built sooner.
2.5hr of hands-on learning ⤵️

Thanks to Miguel Otero Pedrido for inviting me and supporting my content (and the sleek diagram!).

The video has been live for a few weeks.
Now, the full article is available on The Neural Maze Substack.

This gives you a chance to understand the flow better.
Then you can combine it with the video and hands-on.

Let’s build a network with real builders and add value to each other!

📌 Link to the article and video in the first comment

Most people get stuck between learning ML and deploying it.
Here’s the roadmap I wish I had ⤵️

PS: Link for the full YT video below ⭐

— — —

1️⃣ Python Programming
→ The foundation. Everything in ML starts here.
→ clean code, functions, data handling, and reproducibility.

🔗 Python Programming with Mosh (4hours): https://lnkd.in/e_y5APBb
🔗 100 Days of Code: https://lnkd.in/eHQn6HYk

— — —

2️⃣ Math & Statistics for ML
→ Build intuition for algorithms.
→ You can’t optimise what you don’t understand.

🔗 Statistics Fundamentals w/ StatsQuest (playlist): https://lnkd.in/ef3rg2UP
📕 Book: Practical Statistics for Data Scientists

— — —

3️⃣ Machine Learning Fundamentals
→ Learn how models think: data prep, feature engineering, model selection, and evaluation.

🔗 Stanford ML: https://lnkd.in/epviQVc8
🔗 ML specialization (coursera): https://lnkd.in/edbCT-3B
🔗 All ML fundamentals (short overview): https://lnkd.in/eSdDdMWS

— — —

4️⃣ Deep Learning Essentials
→ Understand how neural networks learn and train, from simple perceptrons to CNNs and Transformers.

🔗 MIT intro to deep learning (playlist): https://lnkd.in/ebS2_kvx
🔗 Understanding Deep Learning (notebooks): https://lnkd.in/eUyS-ggD

— — —

5️⃣ MLOps
→ The most in-demand skill today.
→ Automate, version, deploy, and monitor ML systems like a pro.

🔗 Docker for beginners: https://lnkd.in/eQXFqutQ
🔗 FastAPI for beginners: https://lnkd.in/eg7xnhsY
🔗 MLFlow tutorial: https://lnkd.in/enjdQ_zt
🔗 GitHub Actions tutorial: https://lnkd.in/etYr8DDf

— — —

6️⃣ End-to-End ML Projects
→ Bring it all together. Real data, real models, real deployment.
→ This is what turns knowledge into experience.

🔗 Get started with AWS: https://lnkd.in/e98PMn6d
🔗 ML Churn End-2-End (1.5 hours): https://lnkd.in/e3Fmdh3t
🔗 ML Regression End-2-End (2.5 hours): https://lnkd.in/ebMWGweb
📕 Book: Designing machine learning systems

— — —

Happy learning!

🎥 Full video: https://lnkd.in/ekMz9MF8
💬 Comment below: which stage are you currently in?

7 steps to setup Docker for data science projects

(90% of beginners get confused)

1– Choose a base image
→ Start from a lightweight Python version (e.g. python:3.11-slim).

2– Set a working directory
→ Define where your code will live inside the container.

3– Copy dependency file
→ Add only requirements.txt first (helps with Docker caching).

4– Install dependencies
→ Upgrade pip and install your project libraries.

5– Copy project files
→ Bring in your source code and scripts.

6– Expose the port
→ Make your FastAPI or Flask app accessible (commonly port 8000).

7– Define the CMD
→ Tell Docker how to run your app (e.g. start Uvicorn server).


💡 Extra Docker tips for data science
→ Build the image → docker build -t project-name .
→ Run the container → docker run -p 8000:8000 project-name
→ Docker Compose → Manage multi-container apps (API + DB), add volumes to persist data
→ Docker Build Cloud → Up to 39× faster builds for large projects
→ docker init → Auto-generate Dockerfile, compose file, and ignore rules
→ Separate your dev and prod containers


📌 Save this for your next project.
♻️ Share this to help your network in data.

Your Data Science interview is won in the first 15 min
20 questions you must be ready to answer ⤵️ 

Foundations
1. What’s the real difference between correlation and causation, and how do you prove it?
2. Explain bias vs variance as if you’re teaching a new analyst.
3. What are common data leakage examples, and how do you spot them early?

Data Cleaning & Feature Engineering
4. How would you handle missing data differently for categorical vs numeric features?
5. When is scaling not needed, and why?
6. How do you detect multicollinearity and decide what to drop?

Modeling
7. Logistic Regression vs Random Forest: how do you pick one for a real business problem?
8. Explain the ROC curve in plain English. What does AUC actually mean?
9. How do you know your model is overfitting without looking at code?

Experimentation & Evaluation
10. Walk me through how you’d design an A/B test for a pricing change.
11. What metrics would you use for imbalanced classification?
12. How do you deal with data drift after deployment?

MLOps
13. How would you track experiments and compare model versions?
14. What does a good CI/CD setup for ML look like?
15. How do you monitor model performance in production without real labels?

Deployment
16. Walk me through deploying a model with FastAPI + Docker.
17. What’s the difference between batch and real-time inference pipelines?
18. How do you handle model rollback safely?

Communication & Impact
19. You built a model that’s 10% more accurate, how do you explain its value to a non-technical exec?
20. Give an example of when your model was right, but the business didn’t benefit, what went wrong?

⸻
Can you answer these clearly? If not, that’s the gap to fill.

Tip: Record yourself answering these and rewatch. You’ll quickly spot what needs work. Rinse and repeat.

Use the cheatsheet as a starting point, not as an absolute response.

📌 Save this for your interview prep.
♻️ Share this to help your network in data.

Everyone wants to be an AI Engineer.
But not many want to master the foundations first.

Miguel, a Senior ML Engineer, recently told me:
“AI engineering becomes easy when your MLE foundations are strong.”

Still, most people skip the basics like:
→ CI/CD pipelines
→ Feature engineering
→ Model experimentation & tracking
→ Deployment, monitoring & observability
→ Reproducibility (Docker, version control, etc.)

Then they open n8n,
build a few workflows,
and call themselves AI engineers.

I’m not here to tell anyone what to do.
But over the years, I’ve learned to tune out the hype and stick to my plan.

The AI engineers you admire on LinkedIn?

Most have 5+ years of experience in data science and ML engineering.
They didn’t shift into AI overnight.

Stop following the hype.
Start building your career the right way.

77% of data scientists use Pandas for EDA 

Here are 10 tips you need to master today

(PS: This post is focused on pre-analytics)

1️⃣ Use the right function: read_csv, read_excel, or read_sql depending on your source.
2️⃣ Skip unnecessary header rows to start from the actual column names.
3️⃣ Check your file’s encoding (utf-8, latin1, etc.) to avoid weird characters.
4️⃣ Parse your date columns with parse_dates and convert timezones if needed.
5️⃣ Clean numeric columns with commas or symbols before converting to float.
6️⃣ Define missing values properly (na_values=["", "N/A", "-"]).
7️⃣ Remove duplicates with drop_duplicates().
8️⃣ Reset your index after filtering or merging.
9️⃣ Convert mixed types using pd.to_numeric(..., errors="coerce").
🔟 Always inspect data before analysing: df.info(), df.describe(), df.head()

Most analytics still run on tabular data, spreadsheets, CSVs, SQL tables.

Getting these small steps right saves hours of debugging and avoids silent errors that ruin your results.

Do you use Pandas for data analytics?

📌 Save this for your next project.
♻️ Share this to help your network in data.

2 years ago, I pivoted to data science.
I had zero traction.

Today, I reach over 1M people a year.

(Read till the end. I’ll share what actually worked 👇)

I could say it’s easy.
But it’s not.

I started writing on LinkedIn in Jan 2022.
Bought Justin Welsh’s course.
Learned copywriting.

I talked about productivity, then coaching, then data science.

Each time I pivoted, I lost followers.
But I gained friends, real ones.

People who supported me, challenged me, and helped me grow.

LinkedIn has been:
✅ a place to meet amazing people
✅ a place to find inspiration & accountability
✅ a place that forced me to learn and share more
❌ also a place that made me doubt myself at times

Over time, I learned to keep the good and ignore the bad.

So… how can you grow faster (and maybe do even better)?

1️⃣ Stick to ONE topic and go deep
Fluffy content gets likes, not authority.

2️⃣ Be consistent
Consistency makes people:
→ remember you
→ look forward to your posts
→ recognize your tone & style

3️⃣ Join a circle of creators in your niche
→ LinkedIn boosts posts that get engagement from relevant people
→ Genuinely support others, they’ll do the same
→ This alone can 10x your visibility

4️⃣ Don’t compare yourself to others
→ LinkedIn takes time
→ It’s full of noise
→ Follow people who inspire you, and mute the rest

If you can reach 1M people a year in your field, for FREE...
do you really think LinkedIn is a bad investment?

International students, do this before moving to the UK 🇬🇧
(90% of students miss tip #3)

1– Understand your visa options
→ Know the difference between Student, Graduate, Skilled Worker visas, etc.
→ On a student visa, you’re allowed 20 hours of weekly work
→ On a graduate visa, you can freelance, work, or start a business
→ Check working hours allowed, duration, and switching rules early; it’ll save you stress later.

2– Explore part-time and freelance work
→ Many students earn through part-time jobs or freelancing.
→ Start browsing options (e.g., Upwork) before you arrive.
→ I was sold the idea that I could find a part-time job in my field easily (with my engineering background), but it was far from the truth. Do your research.

3– Build your LinkedIn presence
→ Create a clean, professional profile and engage with people in your field.
→ Share your journey, post projects, and connect with UK professionals.
→ This will pay off big time, don’t start late!

4– Get familiar with UK culture
→ Open up to the world. Speak to people. Try different foods. Have fun.
→ You’ll connect faster and feel more confident in conversations and group projects.

5– Set your routine early
→ Bring back your home routine, things that keep you sane.
→ Balance studies with something that keeps you active or creative, sports, gym, etc…
→ It’s easier to stick to good habits than rebuild them after burnout.

—

Do these before you land and you’ll hit the ground running, academically, socially, and professionally.


PS: Full YouTube video in the comments below

Most data scientists don’t fail because they’re lazy.
They fail because they’re stuck learning instead of building.

Here’s why 👇

PS: Full video on YouTube, link in comments

1. 𝗧𝗵𝗲 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝗘𝗳𝗳𝗲𝗰𝘁

You’re trapped in tutorial hell.
You binge courses, follow every trend, and do what everyone else is doing.
You feel busy, but your portfolio looks the same after months.

→ You’re consuming knowledge… not applying it.

2. 𝗧𝗵𝗲 𝗜𝗹𝗹𝘂𝘀𝗶𝗼𝗻 𝗼𝗳 𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀

You think you’re improving, you’re not.
You’re collecting shallow skills with no depth.
A bit of Python, a bit of SQL, a bit of Power BI…
But nothing solid enough to make you stand out.

→ Learning feels like progress, until you try to build something real.

3. 𝗧𝗵𝗲 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝗘𝗳𝗳𝗲𝗰𝘁

Real growth starts when you build.
Pick one complex project that scares you a little.

Learn what’s needed along the way.
Read the docs. Use ChatGPT. Open books.
Stick to a few tools. and master them before adding new ones.

→ That’s how you turn learning into experience.

---

Stop being a content consumer.
Start being a builder.

You don’t need 100 certificates. 
You need one project that changes how you think.

📌 YT video link:  https://lnkd.in/eegvYUdR

If you’ve ever shared a Power BI report, read this.
10 RLS tips that every data analyst must know 👇

1️⃣ 𝗪𝗵𝗮𝘁 𝗥𝗟𝗦 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗼𝗲𝘀
It filters data per user so each person only sees what they should.
Example: a sales manager sees only their region’s sales, not everyone else’s.

2️⃣ 𝗗𝗲𝗳𝗶𝗻𝗲 𝗿𝗼𝗹𝗲𝘀 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗗𝗲𝘀𝗸𝘁𝗼𝗽
Go to Modeling → Manage Roles and add filters like:
[Region] = "UK"

→ Test it with “View as Role” before you publish.

3️⃣ 𝗔𝗹𝘄𝗮𝘆𝘀 𝘁𝗲𝘀𝘁 𝗯𝗲𝗳𝗼𝗿𝗲 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗶𝗻𝗴
RLS doesn’t auto-apply in Desktop, you’ll always see all data by default.
✅ Use “View as Role” to check exactly what each user will see.

4️⃣ Make it dynamic
Avoid static filters, use the user’s email directly:
[Email] = USERPRINCIPALNAME()
This way, each logged-in user only sees their rows automatically.

5️⃣ Use a mapping table for scalability
For large setups, build a user-region mapping table and filter dynamically with USERPRINCIPALNAME())

6️⃣ Why it doesn’t “work” in Desktop
By default, Desktop shows all data because there’s no real login context.
You must test with “View as Role”, that’s the only way to simulate RLS locally.

7️⃣ RLS can be bypassed by permissions
If someone has Build, Edit, or Admin rights, RLS won’t stop them.
Keep those roles to a minimum, use Viewer or App access for restricted users.

8️⃣ Be careful with composite models
If your dataset mixes Import + DirectQuery, RLS may not pass through properly.
Keep RLS on the main model or simplify relationships where possible.

9️⃣ USERPRINCIPALNAME() vs USERNAME()
They look similar but aren’t:
USERPRINCIPALNAME() → returns email (e.g. alex@company.com)
USERNAME() → returns domain\user (e.g. COMPANY\alex)
→ Use the one that matches your organisation’s identity setup.

🔟 Combine multiple filters safely
When you filter by several fields (region, department, etc.), use AND carefully
One mismatch can hide all rows; always test combinations.


RLS is simple in theory but tricky in practice.
Most issues come from missing relationships, wrong functions, or permission levels.

What’s the most frustrating part of RLS you’ve faced in Power BI?

📌 Save this for your next project.
♻️ Share this to help your network in data.

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The Battle

Sahil Bloom

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Sahil Bloom's LinkedIn Performance

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