Building predictive models is the main objective of machine learning (ML), a profession that combines statistics and software development. The world has undergone a rapid transition thanks to machine learning. We need to understand how to interpret the data and draw conclusions because it is expanding exponentially.
We must constantly learn new things to remain at the top of our industry. One of my favorite methods is to pick the brains of more intelligent people, preferably for free. And one of the most significant ways to do this is to follow the top YouTube channels for machine learning. It’s a fantastic resource for knowledge, the newest fashions, and a quick way to pick up new abilities.
We’ll review the best YouTube channels in this article so you can arm yourself with machine-learning skills.
Anyone who enjoys staying current on the most recent research in machine learning will adore Two Minute Papers.
Two Minute Papers creates nearly two-minute-long movies that describe academic papers. Check out the following series if you are interested in the research sector.
One of the most well-liked and effective machine learning YouTube channels is Lex Fridman Podcast. Its host is an AI researcher at MIT and elsewhere who focuses on machine learning, human-robot interaction, and autonomous cars.
Lex discusses all things AI & ML with his guests. He isn’t, though, sticking to just this one theme. He also discusses various topics that motivate you to go beyond your boundaries and inspire, educate, and inspire.
Insights from all the machine learning industry’s top stars, thought leaders, and top scientists. Elon Musk, Nick Bostrom, Andrew Ng, Yann LeCun, Vladimir Vapnik, Matt Botvinick, and many others were among those he spoke with.
This is the most incredible YouTube channel to learn about machine learning if you prefer to grasp things from the ground up.
Sentdex’s owner, Harrison Kinsley, teaches individuals about various technologies, such as Python programming, web development, machine learning, etc.
You should watch the following series created by Harrison Kinsley if you’re interested in learning how each algorithm works, such as how bias and intercept are adjusted at each epoch or how to develop a specific machine-learning algorithm from scratch.
Machine learning aficionados can learn from Kevin Markham, the creator of dataschool.io and the Data School YouTube channel. Kevin’s instruction will help you understand machine learning, regardless of your educational background.
Kevin also creates videos covering various technologies that can be used to build machine learning models, such as pandas, NumPy, and scikit-learn. To fully understand the foundations of machine learning, binge-watch the following Kevin-created series.
On Artificial Intelligence – All in One channel, top instructors like Andrew Ng, Nitish Srivastava, and Geoffery Hinton give top-notch courses.
Text mining, text retrieval, search engines, neural networks, and computer vision are some topics covered in the Artificial Intelligence – All in One course. You might wish to check into the following series, taught by Andrew Ng, to get a good grasp of machine learning concepts.
Phil Tabor is a deep learning and machine learning engineer who makes instructional videos in these fields.
He has put up a fantastic playlist of deep reinforcement learning courses in which he covers the fundamental ideas of the field, including deep deterministic policy gradients in TensorFlow 2, soft actor-critic in PyTorch, robotic control with TD3, and many others.
Jeremy Howard is a data scientist with a background in philosophy. However, out of curiosity, he later combined his stats and programming skills to create the most efficient and user-friendly framework for deep learning jobs.
Suppose you want to develop deep learning models for computer vision tasks like image segmentation, classification, and restoration that need the least amount of coding and produce the best results. In that case, fast.ai is the right choice. Before fast.ai, creating deep learning models was never that simple.
To understand deep learning with the aid of the fast.ai library, you might want to binge-watch the following series.
On YouTube, there is a place called the Kaggle channel where you may explore the Kaggle community, learn, and work on data science projects. The channel provides lectures, thoughtful advice, and conversations with data scientists in its videos.
Regardless of your work sector, this is one of the most incredible machine-learning YouTube channels for anyone wanting to experiment, learn new things, and apply those things to their work.
Xander Steenbrugge is the owner of the channel Arxiv Insights. From a technical perspective, he condenses his main points while making them understandable to a broader audience.
The channel is renowned for its intriguing material, despite the author not regularly uploading videos. Suppose you enjoy ML and AI technical analyses. In that case, this is the spot for you, but you would like a beautiful explanation of the challenging and technical subjects.
Deep Learning is the focus of DeepLearning.TV. The channel offers content on How-Tos, evaluations of software programs and libraries, and interviews with influential people within the industry.
You may learn more about how deep learning operates by watching a series of concept films demonstrating the logic behind each Deep Learning technique.
The focus of the Springboard channel is data science. There are talks on data science and machine learning with professionals from top businesses, a playlist on women in data science with fascinating dialogues with ML professionals, deep dives, or brief tutorials.
This machine learning YouTube channel is fantastic for individuals who want to know how to obtain employment, what to look out for, and what it’s like to work in data science.
Check out the TWIML (This Week in Machine Learning) Podcast YouTube channel if you’re seeking the most recent information from machine learning.
The most intriguing and significant stories from artificial intelligence and machine learning are collected weekly. It’s a fantastic resource for anyone looking to learn more about recent innovations and trends and gain insight from ML specialists.
The Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory’s research is showcased on the MITCSAIL YouTube channel (CSAIL). This channel’s educational material is excellent for people interested in computer science and artificial intelligence. There are many engaging videos showcasing cutting-edge robotics projects and AI research.
In February 2019, Henry AI Labs became a member of the YouTube AI community. This YouTube channel updates the trendiest subjects from academic institutions and major corporations like Google. Natural language processing (NLP), computer vision, reinforcement learning, generative adversarial networks, and other AI and deep learning topics are covered.
The Applied AI Course offers video courses on data science, machine learning, and artificial intelligence. The creation of AI solutions is the main focus of this YouTube channel rather than discussing theoretical computer science. Uber Cab Demand Prediction, Microsoft Malware Detection, and Facebook Friend Recommendation Using Graph Mining are a few of its intriguing AI case studies and initiatives.
This 2014-created YouTube channel features numerous conversations regarding embodied artificial intelligence. This includes films like Computing with a Mess, Biological Robots, 3D Dynamic Scene Graphs, and Certifiable Algorithms for Robot Perception, as well as films like Robots That Reason About Object Semantics, Task Planning and Reinforcement Learning for General-Purpose Service Robots, and Robots That Reason About Object Semantics.
Check out Machine Learning 101, a brand-new ML YouTube channel with explanatory videos on basic AI concepts. The track also airs podcasts with knowledgeable data scientists and people engaged in AI in the private sector.
The non-profit group FreeCodeCamp is fantastic. It is an open-source community that provides various tools so individuals may learn to code for nothing and do their own projects. Anyone can learn how to code on its website for nothing. Additionally, they offer a news site where they post articles about projects and programming.
This YouTube channel aims to increase accessibility for everyone to machine learning and reinforcement learning. For a comprehensive introduction to neural networks for beginners, there is a playlist of 12 videos. It appears that a second intermediate neural network series is now in development.
Data engineer Andreas Kretz founded Plumbers of Data Science. He offers videos with questions and answers about data engineering using Hadoop, Kafka, Spark, and other technologies, as well as live seminars on how to gain practical expertise.
Tim from Tech With Tim is a skilled programmer that teaches Python, Java, Machine Learning, and game creation with Pygame. He also produces advanced Python coding tutorials.
Initiated by Amazon in 2016, Machine Learning University (MLU) has one clear goal: to teach as many staff members as feasible the technology, which is necessary for the business to perform the “magic” of providing products with this integrated technology.
Prathamesh Ingle is a Consulting Content Writer at MarktechPost. He is a Mechanical Engineer and working as a Data Analyst. He is also an AI practitioner and certified Data Scientist with interest in applications of AI. He is enthusiastic about exploring new technologies and advancements with their real life applications
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