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The new buzzword shaking the global business arena is machine learning. It’s grabbed the public’s imagination, conjuring up images of self-learning AI and robots in the future. Machine learning has prepared the path for technical advancements and tools in manufacturing that would have been unthinkable just a few years ago. It drives the breakthrough technologies that sustain our ways of living, from prediction machines to online TV live streaming.
If words like deep learning, neural learning, and artificial intelligence spark your interest, we have a great list of free machine learning courses you can begin with right now.
This is one of the top sites for artificial intelligence courses and it was developed with the aim of teaching the general public about AI, and how to get started in the field of AI. All of the content is created from the ground up with the aim of learning by doing. Beginners and advanced learners can choose from a variety of options.
This Nanodegree program will teach you the skills that all aspiring data analysts and data scientists should have. Examine the entire method of data analysis through the prism of machine learning. Discover how to extract and recognize important features that can be used to better represent your data. You’ll also go over some of the most popular machine learning algorithms and assess their results.
This is the course to which all others in the field of machine learning are measured. For the assignments, the open-source programming language Octave is used instead of Python or R. This may be a deal-breaker for others, but Octave is an easy way to learn the basics of machine learning if you’re a total beginner.
It’s one of the popular free machine learning courses available. The course, which focuses on theory rather than practical implementation, is ideal for beginners who want to learn about machine learning. It contains 18 short lectures that cover topics such as machine learning models, performance, and best practices. There are no preconditions for this course other than a clear understanding of mathematics, so students of all levels are welcome to enroll.
This is an introductory course that only covers the most basic machine learning algorithms. This course employs Python and is less centered on the mathematics that underpins the algorithms. With each module, you’ll have the opportunity to open an interactive Jupyter notebook in your browser and practice the concepts you’ve just learned. Each notebook strengthens your understanding and provides step-by-step guidance for applying an algorithm to real data.
This immersive course is worth a look if you are already familiar with R programming and statistics and want to improve your skills. To begin, you’ll examine the applications and critical issues that this field can solve. You’ll also train and evaluate machine learning models, as well as concentrate on the three basic techniques. After you’ve completed your journey, you can pursue a more advanced specialization.
This one is said to be mandatory reading for everyone at the tech giant who works in AI. This course covers the fundamentals of TensorFlow, Google’s open-source deep-learning library that it uses in many of its own AI-enhanced services and projects, as well as the theory and practical implementations of TensorFlow.
Working for a career as a deep-learning engineer is one of the most exciting careers in IT, and this course offered by Coursera and deep learning. AI is one of the most interesting ways to get started. AI is an excellent primer on the fundamentals of deep learning. Mastering this ability could unlock opportunities you never imagined were possible. So if you’re even vaguely interested, enrolling in this free course should be at the top of your to-do list.
This course will introduce you to core Machine Learning principles, algorithms, and all of the catchphrases you’ve been hearing about Machine Learning. The course is designed not only for people who have a thorough understanding of Machine Learning but also for those who want to refresh their data science skills.
This course will teach you how to master machine learning in Python and R, make predictions, develop a strong understanding of many machine learning models, and work with unique tools such as reinforcement learning, natural language processing, and deep learning. Most significantly, it explains how to select the appropriate model for each issue.
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