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 🧵

Machine Learning for the Web developer in 2021.

The beginner's guide.​

🧵👇

I started machine learning as a web developer, if I can do it then anyone can.

This carefully curated thread will give you key insights into my journey and how you can make this transition, seamlessly.

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"Machine learning is not what you think it is"

One of the main reasons why people find it difficult to get started with machine learning is because of the lack of information, and rightfully so.

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Machine learning as a concept has existed since the 1950s, but has only become popular in recent years because of the exponential rise of advancements in computer hardware.

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In short, it because of the sudden rise of this technology ,which was previously unknown to the general public, that there is a lot of misinformation around it.

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There are several skills needed for learning machine learning that no one talks about.

Here are some of them.
(from what I've learned over the past two years)
🧵👇

This thread aims to introduce to you some of the skills often ignored for learning machine learning but are actually very important.

These skills will enable you to learn concepts quickly and more efficiently in this field.

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1⃣ Reading

Probably one of the most underrated skills on this list.

In machine learning, you HAVE to read a lot of articles, papers, documentation, and whatnot.

It is mostly due to the theoretical nature of this field that reading is an important skill to have.

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2⃣ Strong fundamentals in programming

Machine learning is just a lot of programming mixed with math and data.

Having clear programming fundamentals is crucial for this field.

I highly suggest you learn about these if you are using Python for machine learning.👇

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- Object oriented programming in Python :Classes, Objects, Methods
- Lists & List functions
- Dunder Methods
- List comprehension
- List slicing
- String formatting
- List, Dictionaries & Tuples
- *args,**kwargs

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A simple guide on how to train your first neural network in under 10 minutes to kick-start your machine learning journey.

(+ no setup required and free extra resources)
🧵👇

For this exercise, you'll need :
- A computer/phone
- An internet connection
- Very basic Python knowledge
- Willingness to learn

What you do not need:
- Complex math
- An expensive computer
- A PhD

Math will come later on in your machine learning journey :)

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Here's our problem,we are given data in which we are given the number of flats in a house and its corresponding price. Like a house with one flat is worth 10000, and 20000 for a house with 2 flats.

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We can clearly tell that the price of the house increases by 10000 per extra flat however our computer does not know this and we won't it tell it about this, it'll have to figure things out on its own.

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Here's the code👇

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Are you planning to learn Python for machine learning this year?

Here's everything you need to get started.
🧵👇

In this thread, we'll look at all the concepts in Python you need to know for machine learning along with free resources to help you out.

All of this is based on my experience of successfully teaching 300+ students how to code using Python.

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You can use many languages for machine learning, why Python?

Because of 2 reasons:
- Comparatively easier to learn than other languages
- Has the biggest and most mature community

This makes Python a no-brainer to learn for machine learning as a beginner.

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These are the absolute basics which you must know about:

- Basic terminal commands
- Basic arithmetic (+,-,/,*)
- Accepting user input
- For & While loops
- Exception handling
- If-Else statements
- Functions, modules & Imports

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Then comes the more tougher concepts which you must know about:

- Object oriented programming in Python:Classes, Objects, Methods
- PIP (Pypi)
- List slicing
- String formatting
- Dictionaries & Tuples
- Managing environments
- Dunder methods like __init__

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Everything you need to know about the math for machine learning as a beginner.

🧵👇

Before diving into the math, I suggest first having solid programming skills.

For example👇

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In Python, these are the concepts which you must know:

- Object oriented programming in Python : Classes, Objects, Methods
- List slicing
- String formatting
- Dictionaries & Tuples
- Basic terminal commands
- Exception handling

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If you want to learn python, these courses are freecodecamp could be of help to you.

🔗Basics: youtube .com/watch?v=rfscVS0vtbw
🔗Intermediate :youtube .com/watch?v=HGOBQPFzWKo

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You need to have really strong fundamentals in programming, because machine learning involves a lot of it.

It is 100% compulsory.

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"I want to learn how to code, but have no idea where to begin."

I've been getting this question pretty frequently lately, and thought it was a good time to put together a thread to cover all the basics.

And here it is!

Instead of just throwing a few links at you, I first want to cover something much more fundamental: The *reason* you want to learn to code.

I've had to train a good number of developers in my time. The ones that succeeded had rock-solid, persistent motivations. Is that you?

Some good motivations for learning how to code:

* Enabling a career change
* Insatiable curiosity, eagerness to learn
* Frustration with inefficiency + desire to improve things
* Larger goals in mind, coding being a stepping stone

Some bad motivations for learning how to code:

* It seems popular
* Your friends/family have ideas for apps
* You want to make lots of money by sitting in front of a computer
* You bought an expensive MacBook and are struggling to justify the expense

For those, trade forex.

Motivation matters, because of the one thing that's universally true about coding: It's hard.

Depending on what you do, you may have to learn several languages at once. Tools constantly update. New approaches land in the market on an annual basis. You're constantly upskilling.

I discovered a fantastic GitHub repository called: Projects

This repository contains about 125 project ideas from beginner to intermediate level that anyone can solve in any programming language.

Link - https://t.co/Arl5fl1lQI

Practice and improve your HTML, CSS and JavaScript skills by building these 50 projects.

A thread 🧵

1. Expanding Cards
2. Progress Steps
3. Rotating Navigation
4. Hidden Search
5. Blurry Loading
6. Scroll Animation
7. Split Landing Page
8. Form Wave Animation
9. Sound Board
10. Dad Jokes App

11. Event KeyCodes
12. FAQ Collapse
13. Random Choice Picker
14. Animated Navigation
15. Incrementing Counter
16. Drink Water
17. Movie App
18. Background Slider
19. Theme Clock
20. Button Ripple Effect

21. Drag N Drop
22. Drawing App
23. Kinetic Loader
24. Content Placeholder
25. Sticky Navigation
26. Double Vertical Slider
27. Toast Notification
28. Github Profiles
29. Double Click Heart
30. Auto Text Effect

31. Password Generator
32. Good Cheap Fast
33. Notes App
34. Animated Countdown
35. Image Carousel
36. Hoverboard
37. Pokedex
38. Mobile Tab Navigation
39. Password Strength Background
40. 3D Boxes Background