Are you interested in the latest and greatest advances in machine learning? Then you have come to the right place. In this article, we highlight some of the best YouTube channels for learning about these exciting technologies and disciplines. Keep reading to find the best channel for you! Satisfy your needs by watching the channels, you won't regret your visit!
Machine learning: Top Youtube Channels
Smitha Kolan - Machine Learning Engineer
Smitha Kolan's YouTube channel is dedicated to machine learning and artificial intelligence. She covers topics such as deep learning and Python for machine learning. Her videos are aimed at helping beginners to get started with machine learning and data science. Her videos are clear and concise, and she covers a wide range of topics. If you're just getting started in machine learning, definitely check out her channel.
Learn with Whiteboard
The Learn with Whiteboard channel is all about helping viewers learn about machine learning, digital marketing, brand building, social media, and search engines through whiteboard marketing, programming, and entrepreneurship. Amarpreet Singh is the mastermind behind the channel and he does a great job of breaking down complex topics into easy to understand whiteboard tutorials.
As of now, the channel has 155 videos with over 30,900 subscribers. The videos have a good mix of views and engagement, with the most popular videos having tens of thousands of views.
Tech With Tim
Tech With Tim is a YouTube channel focused on teaching viewers the basics of programming and machine learning through Python. It offers a wide range of tutorials and projects, from beginners' tutorials to more advanced Python machine learning and programming projects. The channel strives to educate viewers on how to use the Python language to build software applications. It is a great resource for anyone interested in learning Python and machine learning.
Great Learning is a popular YouTube channel that covers topics ranging from machine learning, artificial intelligence and artificial neural networks to data science, data analytics, and big data analytics. Through the use of their high-quality data analytics courses, viewers are able to gain a deeper understanding of the latest technologies and trends in machine learning and big data. The videos provided by Great Learning are informative, engaging, and highly educational.
Microsoft Azure is a YouTube channel showcasing how businesses of all sizes can leverage Microsoft Azure's machine learning, artificial intelligence, big data, hybrid cloud and open source capabilities for their digital transformation. Learn how cloud computing and virtual machine technology can help you create an efficient and cost-effective environment for your organization. Get up-to-date on the latest Azure services and strategies from expert industry professionals.
The TensorFlow YouTube channel is a amazing resource to learn about machine learning, artificial intelligence, neural networks, and TensorFlow. It features videos on topics including TensorFlow, TensorFlow Lite, and ML, as well as tutorials and other helpful demonstrations on how to get started with AI and ML. With this, you'll be able to gain a better understanding of deep learning and become a more successful AI and ML practitioner.
StatQuest with Josh Starmer
StatQuest with Josh Starmer is a great YouTube channel for anyone interested in machine learning and data science. Josh does a great job of explaining difficult concepts in a clear and concise way, and the videos are short enough that you can easily watch them in one sitting. I highly recommend checking out this channel if you're looking to learn more about machine learning and data science.
As of now, the channel has 217 videos and 744,000 subscribers. I'm sure it will only continue to grow in popularity, so be sure to check it out!
Lex Fridman's YouTube channel is a resource for anyone interested in learning more about cutting-edge topics in machine learning, deep learning, artificial intelligence, self-driving cars, and AI. It features interviews with leading minds in these fields, as well as interesting podcast episodes exploring the most up-to-date developments.
Siraj Raval is a world-renowned YouTuber who produces content about the newest technologies, such as machine learning, artificial intelligence, deep learning, online learning, decentralized applications, blockchain, AI and Tensorflow. By watching his videos, viewers can learn how to apply these technologies in real-world projects and gain a better understanding of how they work. He is a great source of education and inspiration, pushing the boundaries of what's possible with each new video.
Simplilearn is an educational YouTube channel providing training on a wide range of topics related to digital transformation, such as machine learning, cyber security, digital marketing, data science, six sigma, artificial intelligence, business analyst, deep learning, social media marketing, and ethical hacking. It offers various online learning programs for individuals, teams and organizations. It is an excellent resource for professionals looking to learn in-demand skills.
Codebasics is a valuable YouTube channel that provides programming tutorials on various topics related to machine learning, Python for Data Science, Python, Git, GitHub, coding, and Jupyter. It also has tutorials on Julia Programming to help you learn programming basics and make the most of your machine learning projects.
Data School is an educational YouTube channel focused on providing effective and engaging machine learning and data science tutorials using Python and Pandas. Covering topics from the fundamentals to advanced techniques, Data School provides a comprehensive approach to understanding data, from data manipulation and visualization to machine learning models. With a unique hands-on approach, viewers can learn the skills necessary to become a successful data scientist.
Steve Brunton's YouTube channel is a great source of educational content for anyone interested in machine learning, data science, dynamical systems, fluid dynamics, linear algebra, control, math, and dynamics. He provides detailed explanations and examples to help viewers gain a better understanding of these subjects. There are plenty of educational videos available for those looking to deepen their knowledge and level up their skills in these technical topics.
Vamsi Bhavani's YouTube channel features lectures and tutorials on Machine Learning in Telugu language. It's an educational resource for BTech students to learn and explore topics such as Machine Learning, Mathematics and Computer Science in an engaging and comprehensive manner. He provides an engaging learning experience aided by visual aids in Telugu language. With Vamsi Bhavani's tutorials in Telugu, BTech lectures in Telugu have never been this interesting and informative.
Sentdex is a YouTube channel focused on providing educational machine learning and python programming tutorials. They offer informative how-to videos and detailed instructional material for developing skills in the data science field. Their content is approachable, engaging and offers something for everyone from beginners to seasoned professionals.
Edureka! YouTube channel provides useful training videos and online tutorials on a variety of trending technologies such as machine learning, big data, apache spark, data science, android development, web development, and cloud computing. The videos offer users a high-quality, interactive learning experience.
Krish Naik's YouTube channel is a comprehensive resource for learning about Machine Learning, Deep Learning and AI. It features videos and tutorials on topics like coding, algorithms, natural language processing, and data science. The channel also provides helpful advice and insights into the latest trends in these fields.
Patrick Loeber's YouTube channel is an educational resource for gaining knowledge about machine learning, technology, and lifestyle topics. He focuses on helping his viewers understand and utilize the power of modern technology to improve their lives. With videos covering topics such as artificial intelligence and software development, anyone looking to stay up to date and informed on the latest advances in machine learning and technology can benefit from Patrick Loeber's YouTube channel.
Different Types of Machine Learning
Machine Learning is a form of Artificial Intelligence that enables computers and systems to learn from and adapt to the data they receive from their environment. There are now a wide variety of different types of Machine Learning, allowing for more varied applications of technology.
The first type is Supervised Learning, which involves providing data with correct outputs so that the computer can learn from it. This type of Machine Learning is appropriate for more predictable tasks such as image recognition and facial recognition. It is also useful for creating systems that can respond to data inputs taken from the environment, such as weather forecast systems or self-driving cars.
Unsupervised Learning allows the computer to discover patterns and connections without being given specific data outputs. Clustering is a common form of unsupervised learning that involves grouping data into its component elements, while anomaly detection involves spotting unusual occurrences in the data. This type of Machine Learning is useful for solving problems that require the computer to detect unseen similarities and differences in data, such as fraud detection.
Reinforcement Learning is based on rewarding the computer for achieving a desired outcome, such as winning a game. This type of learning is ideal for tasks that involve optimizing a system’s performance, such as smart energy systems that optimize electricity use. Deep Learning is a subset of Reinforcement Learning that enables the computer to create its own rules and figure out which data inputs are the most relevant towards a certain goal. Deep Learning is useful for speech and voice recognition, as well as natural language processing.
Overall, the different types of Machine Learning enable computers to learn from and respond to the data they receive from the environment, making them more sophisticated and efficient. Each type of Machine Learning involves different methods that can be used to solve a range of problems, making them increasingly valuable in fields such as healthcare, finance and transportation. Despite the variety of different types of Machine Learning, each is well-suited to its own tasks and plays an integral part in Artificial Intelligence.
Algorithms Used in Machine Learning
Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. In order to do this, algorithms are used to learn from data and build models. Algorithms used in machine learning can be split into three groups: supervised learning, unsupervised learning, and reinforcement learning.
Supervised learning algorithms use labelled data sets to predict outcomes. The data is used to asses the relationship between the inputs and outputs, and is then used to classify or forecast new data. An example of a supervised learning algorithm is logistic regression, which is used to classify data points into one of two categories.
Unsupervised learning algorithms use unlabeled data sets to group and classify them. The data is analysed to find similarities and patterns and then classified ad clustered by their relation. An example of an unsupervised learning algorithm is K-means clustering, which is used to group data points into similar clusters.
Reinforcement learning algorithms use a system of rewards and punishments in order to learn from interactions. The system learns from every trial and error it receives and uses this feedback to influence its future decisions. An example of a reinforcement learning algorithm is Q-learning, which is used to simulate complex decisions and optimize outcomes.
Overall, selecting which algorithms to use in machine learning can be a daunting task. But with a bit of experimentation and knowledge of each algorithm’s strengths and weaknesses, you can make the right decision for your desired outcomes.
3 Machine Learning Strategies to Boost Your Business
In today's rapidly evolving digital world, your business needs to stay on the cutting edge of innovation to remain competitive. Machine learning is a powerful tool that can give your business an edge, but understanding how to use it effectively is essential for maximum impact. Here are 3 machine learning strategies that can help you give your business the boost it needs.
- First, focus on creating streamlined data collection processes. By structuring and collecting your data in a consistent way, you’ll make it easier to apply machine learning techniques. This could involve consolidating sources, creating pipelines for data ingestion, or using automated data wrangling techniques.
- Second, use more advanced analytical techniques. Machine learning can do more for your business than just basic linear models. Try exploring new approaches such as Bayesian statistics, neural networks, and reinforcement learning. Investing in the right tools can make it easier to apply more advanced methods.
- Finally, be sure to use machine learning to its full potential. Invest in a retraining and evaluation cycles to ensure your models are continuously optimized. Automate this process so that it takes as little time and effort as possible. Integrate machine learning with existing data pipelines and existing systems to maximize value.
By following these strategies, you can take full advantage of the potential of machine learning and give your business the edge it needs. Start by focusing on data collection and use advanced techniques to fully leverage the power of machine learning. Automate processes to save time and money and ensure your models are consistently performing. With these strategies, you'll be in a position to compete on the cutting edge.