This is a complete guide to start and improve your knowledge of machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques! The complete guide: ​ The GitHub Repository with all the resources: ​ https://medium.com/towards-artificial... https://github.com/louisfb01/start-ma... Follow me for more AI content: Instagram: ​ https://www.instagram.com/whats_ai/ LinkedIn: ​ https://www.linkedin.com/in/whats-ai/ Twitter: ​ https://twitter.com/Whats_AI Facebook: ​​ https://www.facebook.com/whats.artifi... Join Our Discord channel, Learn AI Together: ​​ https://discord.gg/learnaitogether Chapters: 0:00​ - Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 2:33​ - How to start 3:45 -​ YouTube Courses 4:21 -​ Books and Articles 5:00 -​ Maths behind ML 6:00​ - Programming & Online Courses 7:11 -​ Practice, practice, and practice... 8:03​ - Join Communities 8:45 -​ Use Cheat sheets 9:04​ - How to stay up-to-date 9:51 -​ Conclusion Video Transcript 00:00 i get asked these two questions multiple 00:02 times a day 00:03 how can i start in machine learning and 00:06 how can i follow the news in ai 00:08 the first one takes multiple forms such 00:10 as how can i start for free 00:12 how can i start if i don't have a 00:14 developer background or how can i start 00:16 without any math 00:18 etc so i decided to do this video to 00:20 answer them 00:21 once and for all of course since i will 00:24 share many resources 00:25 i also wrote a complete guide on how to 00:27 start in machine learning in 2021 00:30 from no background at all and for free 00:32 as well as a github 00:33 repository with all the useful links it 00:36 is linked in the description below 00:38 because of these pertinent questions 00:40 i've researched a lot of resources 00:42 online and i saved the best ones on a 00:44 notepad over the past 00:45 two years to quickly answer the next 00:47 upcoming questions 00:49 today i will share this notepad with 00:50 everyone and list 00:52 many great resources and give you some 00:54 of my personal tips on how to learn and 00:56 improve your machine learning skills 00:58 and how do i stay up to date with all 01:00 the news in the field 01:02 oh and please let me know in the 01:03 comments if you know any other great 01:05 resources that i could add to this guide 01:07 to make this learning process 01:09 easier and better for everyone since 01:11 this video is a bit special 01:13 here are some important time stamps you 01:15 can skip to if you'd like more 01:16 information about a specific subject 01:19 otherwise i will go through this guide 01:20 and show you how you can develop 01:22 great machine learning skills without 01:24 wasting money following your own needs 01:26 one last thing if you are here to know 01:28 how to stay up to date with the news in 01:30 the field 01:31 and learn about the new techniques you 01:33 should consider subscribing to my 01:35 channel 01:35 since i share exactly this type of 01:37 content every week 01:39 this guide is intended for anyone having 01:41 zero or a small background in 01:43 programming 01:44 mathematics or machine learning this is 01:46 why i will list 01:47 resources for all these subjects but 01:49 feel free to go at your pace and learn 01:51 what you want to learn 01:52 also there is no specific order to 01:54 follow here i mainly listed them the way 01:57 i will do it 01:58 but feel free to start with whatever you 02:00 feel you like the most 02:02 final little note before sharing these 02:04 tips with you 02:05 it is super important do what you want 02:07 to do 02:08 if you don't like reading books skip the 02:10 section if you don't want to follow an 02:12 online course 02:13 you can skip this one as well same thing 02:15 for videos there is not a single way to 02:17 become a machine learning expert and 02:19 with motivation 02:20 you can absolutely achieve it by 02:22 creating your own path 02:23 oh and don't be afraid or ashamed to 02:25 replay videos or learn the same concepts 02:28 from multiple sources 02:29 repetition is the key to success in 02:32 learning something new 02:33 now let's dive right into it this 02:36 section is mainly for complete beginners 02:38 in my opinion the best way to start 02:40 learning anything 02:41 is with short videos on youtube and this 02:44 field is no exception 02:46 there are thousands of amazing videos 02:48 and playlists that teach 02:49 important concepts of machine learning 02:51 for free on this platform 02:53 and you should take advantage of them 02:55 here i recommend two playlists to watch 02:57 they will give you a great first 02:59 introduction to the terms you need to 03:00 know to get started in the field 03:02 the first one is my own playlist where i 03:04 explain the most used terms in the field 03:07 which can be very helpful if you are 03:08 just starting and then 03:10 i'd suggest to dive a little deeper into 03:12 the foundations of machine learning and 03:14 deep learning 03:15 and learn more about neural networks 03:18 understanding neural networks and back 03:20 propagation 03:20 is the most important thing when 03:22 starting and gives you an enormous 03:24 advantage 03:25 when you dive into more advanced 03:27 lectures and courses 03:28 for this i will recommend the great 03:30 playlist made by 03:32 three blue one brown now that you have a 03:34 good basis of what a machine learning 03:36 algorithm 03:37 is how it works and how it learns using 03:40 backpropagation you are ready to dive 03:42 even deeper 03:43 with more complete and advanced courses 03:46 this step is a little longer since you 03:48 will be watching 03:48 many hours of free amazing courses on 03:51 youtube 03:51 and learn a lot from them please do not 03:54 watch these courses while doing 03:56 something else 03:57 they are great resources that need 03:58 concentration taking notes and asking 04:01 questions 04:02 through online communities as i will 04:04 talk later in the video 04:05 here i share three courses that i 04:07 followed and loved personally 04:09 which are the ones from mit stanford and 04:12 andrew angie 04:13 again i just want to remind you that all 04:15 the links are in the repository 04:17 linked in the description below so you 04:19 don't have to note them down 04:20 right away as it has been proven 04:22 multiple times 04:23 humans learn better by repeating and 04:26 learning in different ways 04:27 such as hearing writing reading watching 04:30 and etc 04:32 this is why it's as important to read as 04:34 to watch videos for a better 04:36 understanding 04:37 you will cover many angles and have a 04:39 more complete view of what you are 04:41 trying to learn 04:42 this section is a list of short articles 04:44 and books that are completely free and 04:46 optional 04:47 if you are into reading i will suggest 04:49 starting with these five short articles 04:51 and then 04:52 jump into the more advanced books books 04:54 are a great way to learn at your rhythm 04:56 be sure to understand everything before 04:59 going into practice mode 05:01 the final theoretical subject to cover 05:03 here is the mathematics behind machine 05:05 learning 05:06 which are extremely important you can 05:08 always just apply machine 05:10 learning algorithms and tweak it until 05:12 it works but you will never understand 05:14 it correctly and improve it following 05:15 this path 05:16 if you have zero background in math 05:18 don't worry just like 05:20 most things in life you can learn math 05:22 unfortunately for us 05:24 there's an awesome website called can 05:26 academy 05:27 where you can learn many mathematics 05:29 concepts all for free 05:30 here are some great beginner and 05:32 advanced resources to get into the 05:34 machine learning map 05:36 i also listed some great videos and free 05:38 books you can check as well 05:40 more is better i will also suggest 05:42 starting with these three 05:43 very important concepts in machine 05:45 learning linear algebra 05:47 probability and multivariable calculus 05:50 which are the three courses i suggested 05:53 of course 05:53 if some subjects covered here are 05:55 already a bit too advanced for you 05:57 you can always look to complement these 05:59 with other courses 06:01 or books this section is for beginners 06:03 in coding 06:04 if you have no background at all in 06:06 python or any other programming language 06:08 this will get you starting and give you 06:10 an awesome basis for machine learning 06:12 programming 06:13 if you are already pretty familiar with 06:15 python you can skip to the next step 06:17 here i list the best online courses to 06:20 learn the programming side of machine 06:21 learning using python 06:23 and have a great background but you can 06:25 always decide to learn with another 06:27 language 06:28 for sure now that you have a good 06:30 understanding of the theory behind 06:32 machine learning and a coding background 06:34 you are ready to start your way into 06:36 machine learning courses 06:37 of course these are all optional here 06:40 the first one is free 06:41 and the other ones are paying since they 06:44 will teach you 06:44 many things and some even give you 06:46 certifications you can use in your 06:48 resume 06:49 if you don't want to follow any courses 06:51 you can jump to the next section and 06:53 start to practice on your own 06:55 it will be a little more difficult at 06:56 first but with great googling skills 06:59 and motivation you will be able to do 07:01 this for sure 07:02 otherwise if you prefer to have clear 07:05 steps to follow 07:06 these courses are the best ones to do 07:08 starting from the basics to more 07:09 advanced 07:10 from top to bottom practice practice 07:14 and practice the most important thing in 07:16 programming 07:17 is practice and this applies to machine 07:19 learning too 07:20 it can be hard to find a personal 07:22 project to practice on 07:23 but fortunately for us kaggle exists 07:26 this website is full of free courses 07:28 tutorials and competitions you can join 07:30 competitions for free 07:32 and just download their data read about 07:34 their problem 07:35 and start coding and testing right away 07:38 you can even earn money from winning 07:40 competitions and it is a great thing to 07:42 have 07:42 on your resume as well this may be the 07:45 best way to get experience 07:46 while learning a lot and even earn money 07:49 you can also create teams for kaggle 07:51 competition and learn with people 07:54 i definitely suggest you to join a 07:55 community to find a team and learn with 07:58 others it is always better than learning 08:00 alone 08:01 the following section is devoted to this 08:04 indeed 08:04 most of the time the best way to learn 08:06 is to learn with someone else 08:08 join online communities and find 08:10 partners to learn with 08:12 this is the reason why i created a 08:14 discord server a year ago 08:16 with the goal of getting many ai 08:18 enthusiasts and learn together 08:20 ask questions find kaggle team mates 08:23 share your projects and much more 08:25 it is called learn ai together we are 08:27 already more than 8 000 people 08:29 in not even a year i will be glad to see 08:32 you there 08:33 and please reach out to me if you do you 08:35 can also follow reddit communities where 08:37 you can ask questions 08:39 share your projects follow news in the 08:40 field and more 08:42 here i list the most popular ones that i 08:44 follow on a daily basis 08:46 finally i will recommend you to save 08:48 cheat sheets on your computer 08:49 tablet or even print them they are a 08:52 very good way to compress information 08:54 and have it all at hand here i list the 08:56 best cheat sheets i could find 08:58 and as i just said even if you are 09:00 advanced you should definitely have them 09:02 printed somewhere 09:03 near your desk now another important 09:06 thing in this field is to stay up to 09:08 date with the new upcoming papers and 09:10 new applications that are released 09:12 every single day a great way is to join 09:15 linkedin and facebook groups that are 09:16 sharing these new applications 09:18 you can also follow medium publications 09:20 and youtube channels that are 09:22 summarizing these new papers 09:24 of course you are already at a pretty 09:26 good place for this since i personally 09:28 do share news related to ai every week 09:31 so you should definitely subscribe and 09:33 turn on the notifications to not miss 09:35 any future videos newsletters are also a 09:38 great way to have all the news condensed 09:41 at one place 09:42 every day or week here i list a few of 09:44 the best ones i know that i personally 09:46 use in my day to day life but you can 09:48 surely search for more 09:50 in your fields of interest note that 09:52 this is a non-existent list of resources 09:55 you can definitely use more or less 09:57 resources and learn at your rhythm 09:59 you must follow your instinct to find 10:01 the best way you can learn 10:02 don't ever feel guilty about replaying a 10:04 video or reading an article twice to 10:06 understand a concept 10:08 we've all been through this and it is 10:10 perfectly normal 10:11 the most important thing is that you 10:13 understand the concept 10:14 and not that you go through the list as 10:16 quickly as possible let me know in the 10:18 comments if you know any other great 10:20 resources that i could add to this guide 10:22 to make this learning process 10:23 easier and better for everyone please 10:26 leave a like if you went this far in the 10:27 video 10:28 and since there are over 80 percent of 10:30 you guys that are not subscribed 10:32 yet please consider subscribing to the 10:34 channel to not miss any further news 10:36 thank you for watching 10:46 [Music]

Facebook

Instagram

Super

Twitter

YouTube

Watch more on YouTube: https://www.youtube.com/c/WhatsAI

I explain Artificial Intelligence terms and news to non-experts.

2021 - HackerNoon Contributor of the Year - FACEBOOK

2022 - Best Data Science Newsletter

2022 - HackerNoon Contributor of the Year - Artificial Intelligence

2022 - HackerNoon Contributor of the Year - Computer Vision

2022 - HackerNoon Contributor of the Year - Data Science

2022 - HackerNoon Contributor of the Year - Google

2022 - HackerNoon Contributor of the Year - Innovation

2022 - HackerNoon Contributor of the Year - Machine Learning

2022 - HackerNoon Contributor of the Year - Natural Language Processing

2022 - Top Tech Youtuber

2021 - HackerNoon Contributor of the Year - DEEP-LEARNING

Nominated for 2022 - Best Data Science Newsletter

Nominated for 2022 - HackerNoon Contributor of the Year - Artificial Intelligence

Nominated for 2022 - Top Tech Youtuber

Nominated for 2022 - HackerNoon Contributor of the Year - Innovation

Nominated for 2022 - HackerNoon Contributor of the Year - Data Science

Nominated for 2022 - HackerNoon Contributor of the Year - Natural Language Processing

Nominated for 2022 - HackerNoon Contributor of the Year - Computer Vision

Nominated for 2022 - HackerNoon Contributor of the Year - Google

Nominated for 2022 - HackerNoon Contributor of the Year - Machine Learning

Too Long; Didn't Read

In your car, at home, or at work — Bosch technology shapes many areas of life.

How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML

How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML

Too Long; Didn't Read

Companies Mentioned

Louis Bouchard

About Author

TOPICS

THIS ARTICLE WAS FEATURED IN...

How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML

Too Long; Didn't Read

Companies Mentioned

Louis Bouchard

About Author

TOPICS

THIS ARTICLE WAS FEATURED IN...

RELATED STORIES