What you will learn in this course?
About this course
Machine learning has become a major and integral part of human’s life, having many commercial applications, industrial automation, robotics and research projects are being in continuation of development.
This course is all about machine learning and techniques. Course covers all things about machine learning. What is machine learning. What kinds of modern day problems that we can solve with the help of machine learning. Why are neural networks becoming so popular nowadays? How can you set up your own popular supervised learning problem and find a good, all in one solution using gradient descent and a interesting and thoughtful way of creating datasets? Convert any given raw data files to features in a way that allows Machine Learning to learn important characteristics from that data and bring human insight for problem solving. You will learn how to code distributed machine learning models that is properly scale in Tensorflow, scale out the training of those models and offer high-performance predictions from models made by you. Finally, you will learn how to incorporate and include the right mix of various parameters and boundaries that yields accurate, more précised, generalized models and knowledge of the theory to solve specific special types of Machine Learning problems. You can experiment a lot of things with lot with the help of end-to-end ML techniques, starting from building a simple Machine Learning -focused strategy and progressing into model optimization, training and productionalization with hands-on knowledge and experience of labs using Google Cloud Platform.
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