About this Course
Machine learning is the science of making computers work without explicit programming. Over the past decade, machine learning has given us self-driving cars, active speech recognition, active web search, and the most advanced understanding of human genetics. Machine learning is so common today that you probably use it several times a day without knowing it. Many researchers also consider it the best way to make personal progress toward AI. In this section, you will learn about machine learning techniques that work best, and get used to using them and getting them to work for themselves. Most importantly, you will learn not only about the basics of learning theory, but also the practical knowledge needed to apply these techniques quickly and effectively to new problems. Finally, you will learn about some of the best ways of the new Silicon Valley as it is about machine learning and AI.
This course provides a comprehensive introduction to machine learning, data processing, and mathematical pattern recognition. Topics include: (i) Supervised learning (parametric / non-parametric algorithms, vector support devices, characters, neural networks). (ii) Unsupervised learning (integration, size reduction, recommendation programs, in-depth reading). (iii) Advanced methods of machine learning (bias / variance theory; the process of innovation in machine learning and AI). The lessons will also take you on a number of case studies and applications, so you can learn how to use learning algorithms to build intelligent robots (understanding, control), text comprehension (web search, anti-spam), computer vision, medical informatics, audio, mining, and other places.
Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.
Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.
This is a class that will teach you the end-to-end process of investigating data through a machine learning lens. It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms.
SKILLS TO GET
- Postponement of Items
- Implementation Network Implementation Network
- Machine Learning Algorithms (ML)
- Machine learning
- My SQL
- Computer Vision
For more information you can watch the video,
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