



A subset of artificial intelligence (AI), machine learning (ML) is the area of computational science that focuses on analyzing and interpreting patterns and structures in data to enable learning, reasoning, and decision making outside of human interaction. Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data. If any corrections are identified, the algorithm can incorporate that information to improve its future decision making.





In today's world, having knowledge of machine learning is one of the most integral skills as it can be applied in almost all the fields of IT and CS and is changing all the industries at an unprecedented rate. There is a high demand for ML engineers and programmers as companies want to implement this groundbreaking technology in their products. Additionally, this technology can be used to look at the world in a way that no one has looked before. You may think that learning such a technology may be a hard task but with the help of the resources available, machine learning has become access able to everyone. I am going to review one of the best courses on this subject.









The Machine Learning Course by Stanford on Coursera( https://www.coursera.org/learn/machine-learning?) is a great entry point in the world of machine learning. Delivered by AI and Machine Learning pioneer and Co-Founder of Courser, Mr. Andrew Ng, the course teaches and delivers all the basic concepts of machine learning. Having no pre-requisites, the course can be taken up by the absolute beginners who had never worked in Machine Learning and don't have a background in CS or Mathematics. Mr. Ng excellently simplifies the concepts of machine learning and explains them using simple analogies and intuition.





If you wish to start a career in machine learning, or want to further your knowledge and stay updated with the latest trends, I would wholeheartedly recommend you to take this course. But if you have previously worked in machine learning or want to learn more recent tools like TensorFlow, Keras and Theanos then you sould go with some more advanced course as this course using Octave for programming.