Hustle Hub #23

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Hey friends,

Remember when I asked if you’d think interviewing data experts would be useful to you? Due to the popular demand, I’m very excited to announce that we’ll have our first guest interview today from Michael Dillon who is a Senior BI Developer. 🔥

The guest interview is featured under a new section called Hustler Spotlight. Check it out at the end of this issue!

Moving forward, I’ll invite a data expert to share his/her career journey and insights in our weekly issues. If you want to learn more about their day-to-day life, how they got into the data career, and career tips — you definitely won’t want to miss it.

In today's issue, I’d like to share with you the differences between PyTorch and TensorFlow, how to build rapport with people, and a no-code AI tool — Obviously AI.

Let’s get to it! 🚀 

🛖 What's in the hub today?

• Tip: PyTorch vs TensorFlow: Which Is Best For You?

• Mistake: I faced social awkwardness

• Learning: Relate topics to what people care about

• Book: Rich Dad’s Cashflow Quadrant

• Tool: Obviously AI

⭐️ 1 Tip

PyTorch vs TensorFlow: Which Is Best For You?

I struggled to choose which deep learning framework to learn when I first started in data science. Back then in 2018, Keras (high-level API of TensorFlow) was easy to learn and PyTorch was fairly new, so I decided to go with Keras instead.

Today, PyTorch has evolved a lot and it has become one of the most popular deep learning frameworks in today’s industry. Here comes the question, “Should I choose PyTorch or TensorFlow?”

Since there are many great resources explain the technical differences between PyTorch and TensorFlow, I’ll answer 3 main questions to explain their differences from a career perspective.

1. Which one is easier to learn?

If you’ve been using Python, PyTorch is easier to learn than TensorFlow because its syntax is very similar to Python. Just think of it like you’re using another Python library.

However, if you just want to get started quickly without getting into low-level components, you can learn Keras (Python high-level API for TensorFlow) or FastAI (3rd-party high-level API for PyTorch).

Based on my experience, I personally think Keras is easier to learn than FastAI, but it comes with a lack of control and flexibility. If you want more control or to build custom layers for your neural network, then FastAI is a better option for you.

In short, it depends on the level of technicality and controls you want to have, which would determine which framework is easier to learn for you.

2. Which one has more job opportunities?

In my opinion, having the experience of using TensorFlow would give you more job opportunities in the industry because TensorFlow is built to be an end-to-end machine learning platform, unlike PyTorch which is mainly for the research community to build state-of-the-art models.

However, given the rise of PyTorch in the community, I think PyTorch will slowly catch up with TensorFlow to become a truly end-to-end machine learning platform in the next few years.

In short, TensorFlow has more job opportunities now, but it might be overtaken by PyTorch in the next few years.

3. Which one has better community support?

TensorFlow has better community support as there are many industry professionals and developers who are actively building and using TensorFlow in their company projects.

🤝🏻 Conclusion

If you’re a beginner with zero experience in any deep learning framework, here are my 2 cents:

• Learn Keras (high level) first, then learn how to use TensorFlow (low level).

  • WHY: Keras is easy to learn, and it gives you more job opportunities.

• Learn FastAI (or PyTorch) if you want to keep yourself updated with the latest deep learning models from research.

  • WHY: PyTorch is still more popular in the research community, even though it’s getting widely adopted in today’s industry.

⚠️ 1 Mistake

You might see me as an extrovert because I’m posting actively on LinkedIn, making videos on YouTube, and writing newsletter like what I’m doing here.

But the truth is — I'm an introvert.

If I were to attend a meetup today, my social battery will be drained by the end of the meetup. Most importantly, sometimes I do face social awkwardness — which happened just a few days ago. 😂

I was at an event where I met a new friend (let’s call her Jenny), and for some reason, I asked a bunch of random and stupid questions, which made the whole conversation awkward. Even worst, I couldn’t connect with Jenny to build rapport.

🧠 1 Learning

During the same event, I met another friend of mine (let’s call him Jason). I saw how he was able to connect with new friends easily by talking about the topics that they cared about.

He was always able to build rapport and connect with other easily without making the whole conversation awkward.

🧠 Here’s what I’ve learned:

• Strike a conversation with new friends by relating the topics to what they are doing and care about.

• Have situational awareness and be observant to say the right things at the right time.

• Don’t ask any questions. Ask good questions to show that you care about others.

📚️ 1 Book

Rich Dad’s Cashflow Quadrant

A few years ago, I graduated from college, but I was financially illiterate. Because I thought working for a company is the only way to make money and achieve financial freedom.

After reading Cashflow Quadrant written by Robert Kiyosaki, it helped me understand the unconventional pathway towards financial freedom, and I want to share with you what I’ve learned from the book.

📚️ Here are my takeaways from the book:

• You have to move from Quadrant E (Employee) and S (Self-Employed) to Quadrant B (Business Owner) and I (Investor) — to achieve financial freedom.

  • Buy assets (business & investments) to generate income.

• Solve bigger problems, where bigger financial opportunities lie.

• Know how to differentiate between facts and opinions to make better financial decisions.

• Good Debt vs Bad Debt:

  • Good Debt — Someone else pays for you

  • Bad Debt — You pay with your sweat and blood

• Focus on financial freedom, not job security.

  • Taxes and debts are the 2 main reasons why you will never achieve financial freedom.

🧰 1 Tool

So I chanced upon Obviously AI recently and I thought to myself:

One of the biggest reasons why many SMEs are not adopting ML in their businesses is the lack of technical expertise.

For example, if a sales team wants to identify customers with high-churn probability, they’re not able to do so without a data scientist.

With Obviously AI, many SMEs can finally build ML models without any data scientist to solve their business use cases, resulting in lower cost, fast model prototyping, and shorter time for GTM.

🔥 Hustler Spotlight 🔥

👋🏻 How would you introduce yourself?

‍Hey, I’m Michael! 👋 

I'm a former online poker player, Portfolio Analyst (energy company) and Strategy Analyst (at a bank). Now, I work as a Senior BI Developer in a Consumer Marketing department in Manchester, England.

I always mention the poker experience as it taught me to be very strategic. This is why I enjoy helping people with their job-hunting strategy. For the past year, I’ve been posting daily content on social media to help people land a job in data.

This has turned into podcast appearances, 2 e-books and a newsletter. It’s been so much fun!

👀 What’s your day to day like in your current role as a Senior BI Developer?

‍It’s a mix of setting up new data feeds for different parts of the business, and using the data to develop insights. I use a mix of SQL, PowerBI and a range of other ad hoc tools our company uses third parties to provide.

These days, I’m managing a huge project to transition all of our content to new dashboards. This has led to me managing the project and 3-4 consultants building the dashboards as I design them.

⭐️ What has been the biggest highlight of your career so far?

‍I was a professional poker player for 5 years. I left university and decided I wanted to try it instead of getting a “real” job. It taught me so much about making decisions under pressure, managing emotions, logical decision making and value versus risks.

It taught me how to explain very complex problems into very simple solutions (and break those down further into strategies and tactics).

I’m most proud of that because I use all of these skills every day.

🚀 What's a data or AI trend you're watching this year?

‍I’ve been on the ChatGPT grind like everyone else. I love it.

I used it to create a resume, tailor it to a job, create a cover letter, predict interview questions and generate interview answers. I learned to do all of this in < 15 minutes.

I wasn’t looking for a job, I just wanted to learn the strategy so I could share it with my network and help them.

I packed this entire strategy into a (free) ebook. You can grab your free copy here. It takes about 12 mins to read.

💼 What advice would you give someone starting out in Data Analytics?

Get on LinkedIn and meet people on the same journey as you. In the world of data you can do anything, but you can’t do everything.

Find people on Linkedin who are just ahead of you on the journey (learn from them), who are at the same level (work with them) and just behind you (teach them).

It will make the journey much more fun.

🧠 How would you learn Data Analytics if you had to start over?

3 hours per day.

• 1 hour on DataCamp learning a new concept

• 1 hour creating projects that prove my experience to work at my dream job.

• 1 hour networking with the data community.

🤯 What’s the most important career lesson you wish you’d learned earlier?

No one is coming to save you. Take responsibility for your own development.

In the first couple of years of my career, I used to moan that I wasn’t working on interesting things. I wanted to learn all these new skills but no training was being provided.

To be fair, this was around 10 years ago before the free education boom in data. However, I shouldn’t have been waiting on my boss to teach me anything.

I believe every data analyst should spend 30-60 minutes every day learning something new. Not necessarily for their current job, but just for the sake of following your curiosity.

If you do 1 hour consistently, in six months, you’ll have done 180 hours. Think how much you could learn in that time. That’s 7.5 days of solid learning!

I’d never done that math before, but that’s insane. That would make a great LinkedIn post actually. Be right back.

🔥 Where can we find your amazing work?

I’m back. You got a glimpse into my life there. I got carried away chatting here and boom. I had the idea for this post.

Come say hi on Linkedin here. You can find my free resources here. I’ve got a newsletter called Infinite Upside where I teach people to land a job in data through online networking.

If you sign up soon, you’ll get free access to my upcoming free coaching webinars too.

📚 What's your favorite book?

Never Split the Difference by Chris Voss.

He’s a former FBI hostage negotiator and he wrote this book to help people learn the basics of negotiation for their business careers. It’s incredible.

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to ~1000 subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond