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John Doe

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YouTube Channels To Follow For Artificial Intelligence, Machine Learning And Data Science in 2023

In this post, I am going to share some of the best AI, ML, Deep Learning and Data Science youtube channels that can help you in learning everything from Programming languages (Python or R) to Maths (Linear Algebra, Calculus, Probability, Statistics) to Basic Fundamentals (Intro to AI, ML and DS) to Intermediate & Advanced Concepts.

YouTube Channels for AI, ML, Data Science & Python Enthusiast are

๐Ÿ‘‰ Yannic Kilcher

Yannic Kilcher focuses on explaining deep learning research papers. He introduces the paper and describes the novelty behind it. He reads the paper meticulously to you, and he tells it like a story. He covers topics on deep learning architectures, natural language processing and reinforcement learning. The level of details is incredible. Yannic breaks up a dense paper into parts and uncovers each idea paragraph by paragraph. He explains and scribbles on the screen to walk you through the thought process. When there are concepts not covered by the paper, he references additional resources to reveal any concepts outside of the paper.

๐Ÿ‘‰ Two Minutes Papers

Two Minute Papers is an awesome channel for anyone who loves to be updated with the latest research going on in the Machine Learning domain. Two Minute Papers make 2 minutes (almost) long videos explaining a research paper. If you are keen into research field then you may want to check out the following series

๐Ÿ‘‰ Lex Fridman

Lex Fridman Podcast is one of the most popular and best machine learning YouTube channels. Its host is an AI researcher working on autonomous vehicles, human-robot interaction, and machine learning at MIT and beyond. Lex talks with his guests on everything related to AI and ML. But heโ€™s not limiting himself only to this theme. He talks about other things that can inspire, teach, and push you to exceed your limitations. Insights from all the superstars, influencers, and leading scientists from the world of machine learning. He interviewed such personas like Elon Musk, Nick Bostrom, Andrew Ng, Yann LeCun, Vladimir Vapnik, Matt Botvinick and many more.

๐Ÿ‘‰ Alexander Amini

This channel is for the Deep Learning geeks or for the one who wants to start with Deep Learning and understand it in few weeks, at least that is what the professors are claiming.

The channel offers Deep Learning material from an MIT Universityโ€™s course, packed in 42 videos. It is the best course or one of the best courses out there. The materials start to form the basics and work it way up to how to use it in real-world projects using Reinforcement Learning techniques, NVIDIA, IBM, Googleโ€™s software and more.

๐Ÿ‘‰ Abhishek Thakur

Abhishek Thakur is a chief data scientist, worldโ€™s first โ€œfour times Kaggle grandmasterโ€ . He completely focuses on applied machine learning, deep learning, and data science. He is a great problem solver. His videos on YouTube are just pure magic and it will help you solve problems like a pro. He has also recently published a book on โ€œHow to Approach any Machine Learning Problemโ€ which is an absolute masterclass.

๐Ÿ‘‰ Kaggle

Last by not least, Kaggle, Your Home for Data Science. If Kaggle is where you do and learn, then the Kaggle YouTube channel is where you watch and learn. There are โ€œhow-tosโ€ coding tutorials on deep learning, building dashboards, and data processing. They have live coding sessions on how to solve data science problems.

For updates on the latest NLP research, there is a playlist, Kaggle Reading Group. She reads and discusses NLP research papers. She will explain every single paragraph, diagrams, code, mathematics equations to you. If you are a new researcher or new to academic papers, watch these videos, and you will learn how to dissect papers.

๐Ÿ‘‰ Sentdex

If you are someone who likes to understand everything from scratch then this is by the far the best YouTube channel to learn about Machine Learning. Harrison Kinsley who is the owner of the YouTube channel Sentdex educates people about various technologies included Python Programming, Web-development, Machine Learning, etc. If you are keen to learn every algorithmโ€™s workflow like how does bias and intercept get updated at every epoch, or how to implement a given machine learning algorithm from scratch then you must check the following series made by Harrison Kinsley himself.

๐Ÿ‘‰ StatQuest with Josh Starmer

Statistics and data analysis are a lot easier than most people think. Because computers do the math for you, the most important thing is to understand the concepts and main ideas, and which are made pretty simple by the host Josh Starmer, who makes learning statistics fun. The videos are short, informative and make a great source for those who are starting out in the field of data science, and also to those who need to have a quick look at concepts before an interview.

๐Ÿ‘‰ TensorFlow

This channel is one of the best out there. There are tons of video tutorials explained by the best of the best engineers, the ones who developed TensorFlow. It has tons of videos of conferences where many other engineers, professors, and researchers present their projects. If you are interested in Deep Learning, this is the channel for you. One of the best playlist on their channel is Machine Learning - Zero to Hero by Laurence Moroney.

๐Ÿ‘‰ Jeremy Howard

Jeremy Howard is a data scientist who has an educational background in philosophy but later out of the curiosity he harnessed himself with the knowledge of stats and programming to build the most effective and easy-to-use library for deep learning tasks fastai. Making deep learning models was never that easy before fast.ai came into the picture. If you are someone who wants to build deep learning models that complete the task in the field of computer vision like image segmentation, image classification, image restoration with the minimal coding, and maximum results then the fast.ai is suitable for you. You might wanna binge watch the following series to get a good grasp of deep learning with the help of the fast.ai library.

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๐Ÿ‘‰ Preserve Knowledge

Preserve Knowledge shares selective presentation from conferences such as NeurIPS and interviews with machine learning legends like Geoffrey Hinton and Yann LeCun. Preserve Knowledge covers videos on advances in mathematics, computer science, and artificial intelligence. Its goal is to bring together the world's leading researchers and students in computer science and related fields.

๐Ÿ‘‰ Corey Schafer

Alternative of Sentdex and freecodecamp for learning python for machine learning. On his channel, you will find a huge library of information on Python, Git, development environments, terminal commands, SQL, programming terms, JavaScript, computer science fundamentals, and plenty of other tips and tricks that will help you in your ai or ML career.

๐Ÿ‘‰ DataSchool

Kevin Markham who is the founder of dataschool.io and the owner of the YouTube channel Data School educates machine learning enthusiasts. You can get a comprehensive understanding of machine learning regardless of your educational background thanks to Kevinโ€˜s teaching. Kevin also makes videos that cover several tools like pandas, NumPy, scikit-learn that will help you build your machine learning models. You can binge-watch the following series created by Kevin to get a good grasp of the machine learning fundamentals.

๐Ÿ‘‰ Stanford Online

Stanford University has been at the forefront of innovation for nearly a century. The school has a tradition of pursuing multidisciplinary collaboration aimed at solving the most pressing global problems. On their channel, you will find playlist like Stastics and Data cScience, Deep Multi Task and Meta Learning, Machine Learning with Graphs, Deep Learning and Natural Language Processing and more.

๐Ÿ‘‰ Steve Brunton

Steven Brunton is an associate professor of mechanical engineering and applied mathematics and a data science fellow at the University of Washington in Seattle. To learn all the fundamentals of data science and machine learning, Check out his well known playlist "Intro to Data Science". In addition to this, he has also covered linear algebra used in data science and zipped it in the playlist.

๐Ÿ‘‰ Chai Time Data Science

Led by Sanyam Bhutani, a 2x Kaggle Grandmaster and Machine Learning Engineer at H2O.ai, this channel is must follow after Lex Fridman youtube channel. On his channel, you will find videos like "Learning Data Science - Journey to becoming Kaggle Grandmaster", "Computer Vision & Research at the Dynamic Vision and Learning Group", "Journey to becoming Kaggle Kernels Grandmaster", "The Numerai Story - Building the largest hedge fund" and more.

๐Ÿ‘‰ Computer Science Crash Course

As you can guess from the name, Crash Course is a YouTube channel which consists of different kinds of series which cover important topics related to several fields in an intense manner. These topics include but not limited to sociology, computer science and statistics. The Computer Science series also have videos about Computer Vision and Machine Learning & Artificial Intelligence.

๐Ÿ‘‰ FreeCodeCamp

FreeCodeCamp is an incredible non-profit organization. It is an open-source community that offers a collection of resources that helps people learn to code for free and create their projects. In addition to this, you can also find playlist related to machine learning and data science like Deep Learning with Pytorch, Data Analysis with Python, Data Science 10Hrs Small Course, Videos on Tensorflow, Python and more.

๐Ÿ‘‰ 3Blue1Brown

Mathematics will play a major role in your path to AI or ML or Data Science. If math was not your forte in school than 3 Blue 1 Brown is for you. With its engaging visuals, the channelโ€™s creator works hard to convey complex mathematical topics in the simplest ways for viewers. Topics like probability and statistics will be crucial to your understanding of AI, ML and Data Science.

๐Ÿ‘‰ Daniel Bourke

Going back to school to learn anything is expensive. Nevertheless, the resourceful YouTuber, created his own at home AI curriculum, using the excellent resources available online, and began his path towards AI mastery. For those looking to make the career switch into AI, Daniel Bourkeโ€™s YouTube channel is a great source of inspiration and a healthy reminder that it is possible. His energy is infectious and great place for those looking to forge their own path towards a career in artificial intelligence.

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๐Ÿ‘‰ Data Professor

Data Professor is a YouTube channel of Chanin Nantasenamat. He has done a Ph.D. and is an Associate Professor of Bioinformatics at a Research University where he leads a research laboratory that harnesses data science for unraveling the hidden knowledge of big data in medicine. Here you will get Data Science contents consisting of explainer videos and practical tutorials. The main aim of the channel is to help students and data enthusiasts learn about Data Science and how it can be used to make sense of data.

๐Ÿ‘‰ DeepMind

This is also one of the best channel where you can learn about AI. Artificial intelligence could be one of humanity's most useful inventions. DeepMind aims to build advanced AI to expand their knowledge and find new answers. By solving this one thing, they believe they could help people solve thousands of problems. Some of the best playlist on their youtube channel are Deep Learning Lecture Series, Reinforcement Learning Course and more.

๐Ÿ‘‰ Brandon Rohrer

Brandon Rohrer owns one of the greatest interactive tutorial channels on YouTube. He is a data scientist at Facebook and is clearly aware of what he is talking about. He cuts down on the jargon surrounding data science and conveys the concepts with intuitive real-world examples. If you had to watch one channel to learn and know the language of a data scientist, then it should be this one.

๐Ÿ‘‰ Andreas Kretz

Andreas Kretz is a data engineer and founder of Plumbers of Data Science. He broadcasts live tutorials on his channel on how to get hands-on experience in data engineering and videos with questions and answers about data engineering with Hadoop, Kafka, Spark, and so on.

๐Ÿ‘‰ MITCBMM

CBMM aims to create a new field โ€” the Science and Engineering of Intelligence โ€” by bringing together computer scientists, cognitive scientists, and neuroscientists to work in close collaboration. This new field is dedicated to developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

๐Ÿ‘‰ Jordan Harrod

Jordan Harrod is a graduate student at Harvard and MIT researching brain-machine interfaces and machine learning for medicine. She has always fascinated by the way AI is being integrated into our lives, from social media to the military. In her channel, she explores the way we humans interact with Ai and algorithms, and their uses in our everyday life. Jordan is great at conveying complex topics such as AI to the mass audience and makes it easier to understand. Check out her playlist on AI!

๐Ÿ‘‰ Weights & Biases

Weights & Biases is a company that develops tools for Machine Learning. On their channel you can find presentations by important people in AI and related fields. The topics on their channel include: Machine Learning, Kaggle data science competitions, NLP, Autonomous vehicles, Deep (Reinforcement) Learning, Hyperparameter tuning, the TensorFlow software library, Github platform, Timeseries forecasting, and much moreโ€ฆ

๐Ÿ‘‰ Codebasics

The goal of this channel is to fulfill the vision by teaching the programming in most simplest and intuitive manner. Dhaval teaches simple programming, data science, data analytics, artificial intelligence, machine learning, data structures, software architecture etc on his channel.โ€

๐Ÿ‘‰ MLConf

MLConf is created to host the thought leaders in Machine Learning and Data Science to discuss their most recent experience with applying techniques, tools, algorithms and methodologies to the seemingly impossible problems that occur when dealing with massive and noisy data.

Check out other remaining 20+ Youtube Channels from here: Remaining Youtube Channels

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