I've brought you some amazing GitHub repositories of web development tips and tricks 🌟

THREAD🧵🔽

10 HTML and CSS tips that you need to know😉

🧵👇🏻

1️⃣ Customize the text selection

- The ::selection pseudo-element matches the portion of an element that is selected by a user.

2️⃣ Range Input

- You can change the styling of input type="range"

3️⃣ Custom Scrollbar

- Customize the scrollbar of your website in few minutes

4️⃣ Scrollable element

- If you have some fixed size element then use overflow: auto. It will convert your element into scrollable element

Learn Data Structure and Algorithms for free:

1. https://t.co/b8YeMXWcLF
2. https://t.co/TKkxPKj0Hk
3. https://t.co/WJBl9XU8D9
4. https://t.co/KKEmamdkOI
5.

You are looking to get into Machine Learning? You most certainly can
Because I believe that if an above-average student like me was able to do it, you all certainly can as well

Here's how I went from knowing nothing about programming to someone working in Data Science👇

The path that I took wasn't the most optimal way to get a good grip on Machine Learning because...

when I started out, I knew nobody that worked or had knowledge of Data Science which made me try all sorts of different things that were not actually necessary.

I studied C programming as my first language during my freshman year in college. And before the start of my second year, I started learning python just because I knew C is not the way to go.
I learned it out of curiosity and I had no idea about Machine Learning at this point.

I did not learn python by courses but by books. I'll link all the resources at the end.
The approach I took was just to make the same kind of programs I made in C but just replacing the syntax with that of python and practised those.
Already knowing a language made it easier.

For Machine Learning, the first thing that I did was to join Andrew NG's course which really hit it off for me
I didn't have to have any idea about Machine Learning for the course. I completed that in almost a month and it gave me a good intuition of things and the flow of ML.

I remember how hard it was to find resources for machine learning a couple of years ago.

Now we have so many of them, its impossible for you to not find what you're looking for.

Here are some of them 🧵

1️⃣ Kaggle

My go to place for finding datasets and code snippets, also a great place for discussions.

2️⃣ Papers with code

A collection of the latest and greatest research papers and the best part, a github repository with the code is included!

3️⃣ Kdnuggets

Guides, tutorials and articles on everything AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning.

4️⃣ Towards Data Science

A blog about data science with accessible and well written articles.