With hard work and determination, anyone can learn to code.

Here’s a list of my favorites resources if you’re learning to code in 2021.

👇

1. freeCodeCamp.

I’d suggest picking one of the projects in the curriculum to tackle and then completing the lessons on syntax when you get stuck. This way you know *why* you’re learning what you’re learning, and you're building things immediately.

https://t.co/USHKYI5VHp
2. https://t.co/7XC50GlIaa is a hidden gem. Things I love about it:

1) You can see the most upvoted solutions so you can read really good code

2) You can ask questions in the discussion section if you're stuck, and people often answer. Free mentorship!

https://t.co/bX28PngH4i
3. https://t.co/V9gcXqqLN6 and https://t.co/KbEYGL21iE

On stackoverflow you can find answers to almost every problem you encounter. On GitHub you can read so much great code. You can build so much just from using these two resources and a blank text editor.
4. https://t.co/xX2J00fSrT @eggheadio specifically for frontend dev.

Their tutorials are designed to maximize your time, so you never feel overwhelmed by a 14-hour course. Also, the amount of prep they put into making great courses is unlike any other online course I've seen.
5. https://t.co/7MU2nHpsz2

This site is so much fun!

Especially if you feel intimidated or bored by other coding sites. It's an addicting game and you can choose what language you want to learn (JavaScript, Python etc)
6. https://t.co/uAAqbI9iTW

Similar to freeCodeCamp and has tracks in JavaScript, Ruby, HTML + CSS, node, etc. The courses have a good roadmap that takes you step by step and build up your knowledge.
7. https://t.co/JwwBlncZZF

For frontend development. These workshops are special. One of my favorite things about them are the live questions that teachers answer throughout the workshops. If you join a live workshop you can interact with your teacher, which is pretty awesome.
8. Colt Steele's Web Dev Bootcamp course.

For so many people, this teacher inspired them to get into coding and left them with the belief that they could do it. Colt's courses are magical.

https://t.co/GJgg2Adi06
I specifically left this list as short as possible because I don't think it's helpful to be bombarded with a list of 101 resources. That can be overwhelming. Lastly, I hold group coding sessions where we tackle coding problems every Sunday in @CodeBookClub!

More from Machine learning

This is a Twitter series on #FoundationsOfML.

❓ Today, I want to start discussing the different types of Machine Learning flavors we can find.

This is a very high-level overview. In later threads, we'll dive deeper into each paradigm... 👇🧵

Last time we talked about how Machine Learning works.

Basically, it's about having some source of experience E for solving a given task T, that allows us to find a program P which is (hopefully) optimal w.r.t. some metric


According to the nature of that experience, we can define different formulations, or flavors, of the learning process.

A useful distinction is whether we have an explicit goal or desired output, which gives rise to the definitions of 1️⃣ Supervised and 2️⃣ Unsupervised Learning 👇

1️⃣ Supervised Learning

In this formulation, the experience E is a collection of input/output pairs, and the task T is defined as a function that produces the right output for any given input.

👉 The underlying assumption is that there is some correlation (or, in general, a computable relation) between the structure of an input and its corresponding output and that it is possible to infer that function or mapping from a sufficiently large number of examples.

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हमारे ऋषि मुनि विद्वान थे, वे जो बात करते या कहते थे उसके पीछे कोई न कोई वैज्ञानिक कारण छुपा होता था।

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इमारत, पर्वत या अट्टालिकाओं पर ज़रूर देखा होगा। देखा है न?

ज़रा सोचिये पीपल या बरगद की बीज कैसे पहुंचे होंगे वहाँ तक? इनके बीज इतने हल्के भी नहीं होते के हवा उन्हें उड़ाके ले जा सके।