Tweet

How to get URL link on Twitter App

On the Twitter thread, click on or icon on the bottom
Click again on or Share Via icon
Click on Copy Link to Tweet
Paste it above and click "Unroll Thread"!
More info at Twitter Help

Akshay 🚀

@akshay_pachaar

Jul 26 • 6 tweets • 3 min read Twitter logo

Read on Twitter

Scrolly

Microsoft is offering FREE courses in following areas:

- AI
- IOT
- Data Science
- Machine Learning

A project-based pedagogy that allows you to learn while building! 🚀

Read More ...👇

1️⃣ AI for beginners

A 12-week, 24-lesson curriculum all about Artificial Intelligence.

You'll learn about:
- Neural Nets
- Deep Learning
- Knowledge representation
- Genetic Algorithms & multi-agent systems

Check this out 👇
https://t.co/rZ3Jdw2Le8microsoft.github.io/AI-For-Beginne…

2️⃣ IOT

Learn about IOT by doing project that cover the journey of food from farm to table.

This includes farming, logistics, manufacturing, retail and consumer - all popular industry areas for IoT devices.

Check this out 👇
https://t.co/o4GJM8gHzmmicrosoft.github.io/IoT-For-Beginn…

3️⃣ Machine Learning

A great course on classical machine learning, using Scikit-learn!

Check this out👇 https://t.co/vpUIczCZ5Tmicrosoft.github.io/ML-For-Beginne…

4️⃣ Data Science

This course covers Deep Learning & Data Science in more details!

Each lesson includes:
- hands-on assignments
- pre & post-lesson quizzes
- instructions to complete the lesson & solutions

Check this out👇
https://t.co/YmOsSEWr7Cmicrosoft.github.io/Data-Science-F…

That's a wrap!

If you interested in:

- Python 🐍
- Machine Learning 🤖
- Maths for ML 🧮
- MLOps 🛠
- CV/NLP 🗣
- LLMs 🧠

Find me → @akshay_pachaar ✔️

Subscribe to my Newsletter→

Everyday, I share tutorials on above topics!

Cheers!mlspring.beehiiv.com/subscribe

• • •

Missing some Tweet in this thread? You can try to force a refresh

This Thread may be Removed Anytime!

Twitter may remove this content at anytime! Save it as PDF for later use!

More from @akshay_pachaar

Akshay 🚀

@akshay_pachaar

Jul 25

Better prompts lead to better responses from LLMs!

But how do you decide which prompt is better❓🤔

Let me show you how it's done:

So, how prompt selection is done ?

An LLM is tested on a certain test dataset using different prompt templates & the performance is evaluated.

The challenge with real world data is that it can be noisy.

Check this out👇

Today, there are various ways to prompt LLMs.

Here are a few standard techniques:

- Few Shot prompting
- Instruction prompting
- Templatized prompting
- Chain of thoughts prompting

Images below provide example for each 👇

Read 8 tweets

Akshay 🚀

@akshay_pachaar

Jul 24

Two of the fundamental evaluation metrics in machine learning are:

- Precision
- Recall

But, their formal definitions can be a bit confusing.

In next 2 minutes I'll help you clearly understand them!

Let's go!🚀

Let's say there are 10 people in a Town.

2 of them have committed a crime, so in reality:

- 8 are innocent
- 2 are guilty

This is how it looks 👇

Now, we hire a detective to catch the guilty parties!

The detective accuses 3 people of being guilty, while 7 are deemed innocent.

Out of the 3 accused, only 1 is actually guilty.

Out of the 7 predicted innocent, 1 is guilty in reality.

This is how the scenario looks so far👇

Read 8 tweets

Akshay 🚀

@akshay_pachaar

Jul 16

Harvard university is offering FREE world class education in Data Science!

Courses cover:
- Python
- Data Visualization
- Probability
- Statistics
- Machine Learning
- Data Science: Capstone

A project-based pedagogy that allows you to learn while building! 🚀

Read more!👇

1️⃣ CS50p: Python

If you are new to programming and just getting started.

There isn't a better place to learn Python than @davidjmalan 's CS50p.

Beautiful explanations and great projects.
It's a complete package.

Check this out 👇
edx.org/course/cs50s-i…

2️⃣ Data Visualization

Learn basic data visualization principles and how to apply them using ggplot2.

Check this out👇
edx.org/course/data-sc…

Read 8 tweets

Akshay 🚀

@akshay_pachaar

Jul 15

LLMs have taken the world by storm, and attention is everywhere!

It's about time we understand how things work!

Today, I'll clearly explain the self-attention mechanism!

Let's go! 🚀

Computer are good with number❗️

In NLP we convert the sequence of words into token & then token to embeddings.

You can think of embedding as a meaningful representation of each token using a bunch of numbers.

Check this out 👇

Now, for a language model to perform at a human level, it's not sufficient for it to process these tokens independently.

It's also important to understand the relationship between them!

Check this 👇

Read 9 tweets

Akshay 🚀

@akshay_pachaar

Jul 14

Decorators are one of the most powerful feature of Python! 🔥

However, understanding them can be a bit overwhelming!

Today, I'll clearly explain how decorators work!

Let's go! 🚀

Before we jump onto decorator, we must understand that functions in python are "first-class" objects!

It means that a function can be:

- passed around as an argument
- used in expressions
- returned as values of other functions

Just like integers or string!

Check this out👇

To get the essence of Decorators, let's imagine it's your friend's birthday, you're giving them a gift.

But before you do, you wrap it in a fancy gift paper to enhance its look, right?

Decorators do the same thing but with functions. ✨

Let's see how ... 👇

Read 8 tweets

Akshay 🚀

@akshay_pachaar

Jul 10

Embeddings are the building blocks of powerful LLMs we see today!

Let me break things down to first principles & also show you how to harness power of embeddings!

Let's go! 🚀

So, what are embeddings❓🤔

Vector embeddings are a way to represent data (image, text, audio) as a series of numbers.

Think of it like turning words into a special kind of code that computers can understand and work with more easily.

Check this 👇

Why embeddings are so powerful:

- They capture meaning
- They reveal relationships
- Allow similarity search
- Save space

The image below is a great example of how meaning & relationship is captured in form of vectors/embeddings 👇

Read 6 tweets

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Share this page!

Enter Twitter Thread URL to Unroll

Akshay 🚀

Try unrolling a thread yourself!

More from @akshay_pachaar

Akshay 🚀

Akshay 🚀

Akshay 🚀

Akshay 🚀

Akshay 🚀

Akshay 🚀

Did Thread Reader help you today?

Don't want to be a Premium member but still want to support us?

Send Email!