Learn Machine Learning in 3 Months (with curriculum)

Learn Machine Learning in 3 Months (with curriculum)


Brace yourself you’re, about to feel to learn so hard hello, world it’s suraj And the question i get asked the most by far is how Do i get started with machine learning I’ve created a three-month guide to help you go from an absolute beginner to Proficient in the art of machine learning and i’ll describe it in this video It’s for those, who can Only dedicate part time to learning since you either a Have a job or B have to go to school but your if you’re able to go full-time you can complete this in half the time This, is something that i create for myself if i were to start learning, ai today but i’m open Sourcing it for you to help you out let’s start By looking at the hiring page for deep mind arguably the World’s leading institution when it comes to publishing state-of-the-art Ai algorithms if we look under the research engineer position we’ll see a description for what it takes to be a part of the team responsible for alphago, the deep q network And wavenet each of which revolutionized the field of ai the minimum? Qualifications are having a bachelor’s in computer science or a related field strong knowledge of python machine learning and algorithmic design no need
to Have a phd or have published a ton of papers even under the preferred Qualifications if we were to create a pie chart to try and understand the necessary Topics for machine learning it would look something like This thirty, five percent of it would consist of linear algebra twenty five percent, would include probability theory and statistics Fifteen percent, would be calculus another fifteen percent Would be algorithms and complexity and the last ten percent, would be dedicated to data pre-processing Knowledge, we can build our own curriculum around this chart wait where to begin I’ve divided this curriculum up into three months the first month consists of math and algorithmic Complexity the second month consists of machine learning And the third month consists of the most popular subset of machine learning deep learning but Before we begin i want to first say that one of your daily? Tasks, should, be to keep up with the field so here are the best resources to do that First is my youtube channel i’m going to be pushing ai content here Non-stop every single week so hit the subscribe button to get notified of new content if you haven’t yet Next is the machine learning subreddit it’s a place where people Working both in academia and in business on ml share their findings twitter is also a really underutilized Resource twitter acts like a learning feed if you Use it the right way follow really smart people and scrolling down Your feed unlike most social platforms Won’t drain you in fact it will enrich you with knowledge ml researchers love To, use twitter there are some really good academic debates that happen there as Well some examples of researchers i follow, are ilya sutskever trent mcconaughey andrej, carpathia andrew Trask petera biel chris ola and nando de freitas there are many more i’ll link to them in the description Hacker news is another must-have the audience is well versed in the technical details of the topics mentioned? So you know that the only the best arguments rise to the top all of the resources i suggest are? going
to Be video based i just learned so much better using videos and short form written Content on the web and by using a plain text book, that just lists equation after equation after equation With no real-life application now on to the first month Learning the math we’ll start with the portion that makes up the most of machine learning linear algebra one of the most popular courses on mit Opencourseware website is the linear algebra course Taught, by gilbert strong he’s got a kind of infectious enthusiasm for this stuff and there are 35 video lectures available On youtube as a playlist watch, each one at 2x speed if possible 3x if you can handle it take the time to handwrite your notes as you watch Not necessarily for your record, but just ingrain what you’re learning into. Your head that much more efficiently studies show That taking notes by hand really does enhance your brain’s ability to retain the concepts you’re learning then you can move on to calculus 3 blue 1 Brown has an incredible playlist called the essence of calculus Grants a friend of mine and i can vouch for his work he’ll teach you calculus in a way that makes you feel like you Could have invented it yourself, and when it comes to probability and statistics Edx has a really good course called the science of uncertainty taught, by mit you’ll Also find an awesome course on algorithmic design and analysis on edx taught by upenn Dedicate a week to each one of these courses even though, they, say they take, longer we’re. Practicing what’s called accelerated learning two to three hours every single day of undistracted Absorption you are going to be like a sponge Watched a lecture at a faster speed Take notes as you Go and complete one project at the end of every week preferably one of the harder ones at the end of the course to complete yourself Each of these subjects has a one-page cheat sheet you can find on the web anyway don’t feel bad if you complete a course Faster than what the authors suggest Learning is just about downloading data into your brain you can, use tools to accelerate that process Now we’re ready for month two Machine learning i’ve got three playlists for you to watch in order learn python for data science the math of intelligence and intro to tensorflow Then check out udacity z– free intro to machine learning. Course it’s pretty Well made for the next two weeks you’re, gonna pick some cool machine learning projects to complete and code them yourself using python i’ve got a great compilation of ideas in the form of a Github, link to help you this is gonna help you develop a sense of when to use a specific Machine learning model and how it would work for an application specific Use case i also recommend Participating in a casual competition it’s a great way to learn and earn money at the same time it’s this ability to categorize Certain types of problem certain types of machine learning models that well-paid machine learning consultants provide for companies if you can build this intuition yourself, you’ll be much better off I’d suggest picking and choosing two projects a week and building Each from scratch, this will give you hands-on experience with the pillars of machine learning including optimization data pre-processing Types of learning data set splitting and model evaluation This is all about turning sponge mode into code and a lot of the art of data science Lies in the dozens of micro decisions you’ll make to solve a specific Problem this is the perfect Time to practice making those micro decisions and evaluating the consequences of each side can’t learn is a really easy Framework to quickly implement, some machine learning models you’ll find that over time to complete a problem you’ll be asking Yourself the same questions how To, best split the data what are the best parameters etc at the end of this month you should give yourself a final project And that would be to code up the simple gradient descent algorithm from scratch it’s the most used Optimization strategy in machine learning if you can, code this from scratch Literally everything, else becomes easier alright on to the third Month, deep learning the specific algorithm called a neural network When given vast quantities of data and vast amounts of computing power Outperforms almost everything, else almost every time, and that’s why it’s so popular Check out my intro to deep learning course on youtube then check out fast ais deep learning course 36 hours of high quality Lessons for free for the last two weeks just implement deep learning app after deep learning app Over this time period you should have at least 5 to 10 projects related to machine learning and deep learning on your github You’ll be surprised how, fast you can go from learning, about simple perceptrons to state-of-the-art Models the difference being usually just a few minor tweaks in the architecture the deep learning space as of now Is rich with, technical literature and some of the best stuff is free At the end of these three months you should feel confident enough to take your knowledge and either a work in the field as a Machine-learning engineer b start a consulting firm or c start your own product based ai Company just figure things out as you go stop, telling yourself that you can’t learn it or you’re Not smart enough remember learning is a life Long process no matter how old you are or where you’re from you can get to the point, where you can Make an impact in this field thanks to the internet and look if you, don’t like, my learning plan make your own Do what suits you best And better yet get a friend to commit to the same learning path as you that way you can keep each other in check and not drop out as long as you’re, giving, yourself positive feedback Along, the way you won’t give up, ai is going to eat every single industry and change what it Means to be human it’s all happening very very fast either you understand it or you don’t, which side do you, want to be on? Same so get started on your learning, journey i’m rooting for you wizard Please subscribe for more ai and blockchain videos and for now i’ve got a course to launch so thanks for watching

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