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How to get into AI + Facebook AI reading list (the best resources)
Hi, I'm Oleksii and I work at Facebook AI Research. The list of the best resources to learn ML and AI is right here.
========== Stage 1 ==========
-Theory:
Linear Algebra, Statistics, Theory of Probability (any courses/books will work)
-Practice:
Basic Python skills, NumPy
========== Stage 2 ==========
-Theory:
Online courses / books on ML and Deep Learning;
Machine Learning course by Andrew Ng, Coursera;
Deep Learning Book, Goodfellow;
Stanford CS231n course;
Recent MIT course: https://introtodeeplearning.com/;
https://www.fast.ai/
-Practice:
Pandas, PyTorch, Tensorflow and "official" tutorials (form their websites)
========== Stage 3 ==========
-Theory:
"Classic" papers, e.g. AlexNet, ResNet, BERT;
Reading lists:
https://deeplearning.net/reading-list/
https://github.com/ujjwalkarn/Machine...
https://github.com/floodsung/Deep-Lea...
MILA reading list: https://docs.google.com/document/d/1I...
Andrej Karpathy's blog: https://karpathy.github.io/
-Practice:
Random tutorials on the internet, Advanced tutorials, replicating papers
========== Stage 4 ==========
-Theory:
New paper on your topic, conferences, ArXiv, mailing lists and news channels;
https://distill.pub/;
Sebastian Rudder: https://newsletter.ruder.io/ ;
THE BATCH: https://www.deeplearning.ai/thebatch/
-Practice:
Working on toy-projects;
Contributing to open-source projects;
Getting an internship;
Trying to get hands-on experience in any way possible
========= Never Stop =========
These all will be usefull for anyone, engineer or researcher. Also try to concentrate on one particular topic and get an expert in it first, it will be much easier to accomplish and will open you opportunities right away. Don't try to become an expert in everything and also do not neglect "not prestigious" experience. Any experience is very valuable.
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Mental Resilience
Building your "mental resilience" as you head into a world where you will need to continue to reinvent yourself to leverage/compete with artificial intelligence - continually making yourself relevant. To do so, you need to gain data science expertise; again an understanding how best leverage artificial intelligence/machine learning capabilities and applications.
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Why the rise of AI makes "mental resilience" so important
Israeli historian Yuval Noah Harari explored the past and future of humanity in his books "Sapiens" and "Homo Deus." They became international bestsellers and were praised by a wide-range of thought leaders, including former President Barack Obama and Bill Gates. In his new book, "21 Lessons for the 21st Century," Harari focuses on the present and dissects the most pressing issues facing humanity. He joins "CBS This Morning" to discuss why it's important to teach children "emotional intelligence" and "mental resilience" as they head into a world where they will need to continue to reinvent themselves to compete with artificial intelligence.
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Watch me Build a ...
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Watch Me Build an AI Startup
I'm going to build a medical imaging classification app called SmartMedScan! The potential customers for this app are medical professionals that need to scale and improve the accuracy of their diagnoses using AI. From ideation, to logo design, to integrating features like payments and AI into a single app, I'll show you my 10 step process. I hope that by seeing my thought process and getting familiar with the sequence of steps I'll demonstrate, you too will be as inspired as I am to use this technology to do something great for the world. Enjoy!
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How to Start an AI Startup
How are you supposed to get in on the AI hype? Deep Learning has enabled a whole new breed of applications, and there are still so many different opportunities to apply it in fields that are completely untapped. I'll go through the steps you need to take to start your own AI startup using a combination of my own experiences and best practices from the industry as a guide. From data collection to model training to picking a problem, we'll try to understand this challenging task.
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Make Money with Tensorflow 2.0
I've built an app called NeuralFund that uses Tensorflow 2.0 to make automated investment decisions. I used Tensorflow 2.0 to train a transformer network on time series data that i downloaded using the Yahoo Finance API. Then, I used TensorFlow Serving + Flask to create a simple web app around it. I'll explain what the important parts you should know in Tensorflow 2.0 are, then I'll guide you through my code & thought process of building an AI startup using it. Enjoy!
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7 Ways to Make Money with Machine Learning
Machine Learning is an amazing technology, but how are you supposed to earn a living from it? In this video, I'll break down 7 ways that anyone can earn money from anywhere in the world using machine learning. Well start by taking a look at whats called the "AI Value Chain" to learn who is currently making money in machine learning so that we can better chart out where we can contribute to the space. From startups, to competitions, to writing books, we've got a lot to cover in this video. Enjoy!
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How to Do Freelance AI Programming
You can build a sustainable full-time income from doing freelance AI programming work. In this video, i'm going to show you the steps you can take to start your journey as a freelancer. Whether you're a student or are employed full-time, you can begin the process of planning out a freelance career today. Getting clients, leveling up your skills, marketing yourself, setting up your financials, tools to help optimize your workflow, these are all aspects of the freelance life that i'll explain from my own personal experience.
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How to Make Money as a Programmer in 2018
I'll go through 5 methods that you can use to make money as a programmer! We are lucky in that our skill will only get more valuable to society over time. Links to everything I've discussed are below.
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Learning Approaches
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The Fastest Path To Deep Learning
Learning Deep Learning can be confusing and often very frustrating. In this talk, Sam will set out a roadmap to go from knowing nothing to being fluent in Deep Learning in the fastest way possible. He will highlight courses, frameworks, math, methods, and strategies to get you started and set you on the path to being able to use Deep Learning for real worlds problems and apps. EVENT: FOSSASIA 2018 SPEAKER: Sam Witteveen, Machine Learning Developer Expert Google
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How I'm Learning AI and Machine Learning
For the past 6 months or so, I have been teaching myself about artificial intelligence. In this video, I describe some of the places I learned from and a few of the things I've done with my new found knowledge. Lots of my AI code: https://github.com/unixpickle/weakai
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Learning AI and ChatGPT isn’t that hard
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How to Learn Deep Learning (when you’re not a computer science PhD)
Talk video from meetup April 11, 2017 at AWS office in SF. Huge thanks to Amazon for providing venue, food/drink, and video recording! Abstract: Many people claim that Deep Learning needs to be a highly exclusive field, saying that you must spend years studying advanced math before you even begin to attempt it. Jeremy Howard and I believed that this was just not true, so we set out to see if we could teach Deep Learning to coders (with no math prerequisites) in 7 part-time weeks. Our students are now using Deep Learning to identify chainsaw noise in endangered rain forests, create translation resources for Pakistani languages, reduce farmer suicides in India, diagnose breast cancer, and more. We wanted to help them get results fast, so we taught them in a code-centric, application-focused way. I’ll share what we learnt about how to learn Deep Learning effectively, so that you can set out on your own learning journey. [[Creatives#Rachel Thomas|Rachel Thomas]
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Learn Machine Learning in 3 Months (with curriculum)
How is a total beginner supposed to get started learning machine learning? I'm going to describe a 3 month curriculum to help you go from beginner to well-versed in machine learning. Its an accelerated learning plan, something i'd create for myself if I were to get started today, but I'm going to open source it for you guys. This curriculum will cover all the math concepts, the machine learning theory, and the Deep Learning theory to get you up to speed with the field as fast as possible. If anyone asks how to best get started with machine learning, direct them to this video!
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How to Study Machine Learning
Let me show you the techniques I use to study machine learning in this video. That includes living a healthy lifestyles, optimizing your learning environment, creating a personalized learning path, prioritizing effectively, and being an active learner. I'll demo the FAST technique, which you can use to help learn faster and more efficiently. I made this with machine learning technology in mind, but these techniques can be used for any field. Enjoy!
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