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Applications of Machine Learning Real world examples of Machine Learning


Applications of Machine Learning Real world examples of Machine Learning This Learnaholic India video will cover: Applications of Machine Learning Examples of applications of machine learning Application of ML in Augmentation, Applications of ML in Automation, Applications of ML in Finance industry, Applications of ML in Government organisation, Applications of ML in Marketing, Applications of ML in Healthcare industry, Machine Learning is a system that can learn from example through self-improvement and without being explicitly coded by programmer.

Top 10 Machine Learning Algorithms for Beginners Machine Learning Tutorial [Data Science]


This Machine Learning Algorithms Tutorial video by Learnaholic India will help you learn Machine Learning Tutorial, what is Machine Learning, [Data Science] various Machine Learning problems and the algorithms, key Machine Learning algorithms with simple examples. The key Machine Learning algorithms discussed in detail are Linear Regression, Logistic Regression, Decision Tree, Random Forest and KNN algorithm. Machine Learning Tutorial [Data Science] Top 10 Machine Learning Algorithms for Beginners In this Machine Learning Algorithms Tutorial video you will understand: 1) Types of Machine Learning Algorithms (00:25) 2) Supervised Learning Algorithms (00:30) 3) Unsupervised Learning Algorithms (1:59) 4) Reinforcement Learning Algorithms (3:38) 5) Top 10 Machine Learning Algorithms for Beginners (4:33) This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a data-set for model creation and validation and how you can create a model using any machine learning algorithm! Hit the subscribe button above.

All about Artificial Intelligence AI Careers Skills needed for a career in AI


" All about Artificial Intelligence / AI " by Arish Ali, CEO at Neurofy This video covers - Basics of Artificial Intelligence - Artificial intelligence in India - AI revolution across Industries - Careers in AI - Skills needed to make a career in AI Do check out our "PG Certificate Program in Artificial Intelligence & Deep Learning" course AI and Deep learning have shown promising growth in recent years and in the near future can change the way companies operate. After completing the Deep Learning and Artificial Intelligence online course, you'll be able to: - Use Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools.

Are Emerging Technologies for Women? How to Become a Data Scientist Data Analyst or AI/ML Engineer?


This International Women's Day, we have a treat for our Women viewers; A special career advice video that will pave the path for your career transitions into Data Science, AI, Machine Learning and Data Analytics. In this video, our star women mentors from Swiggy, G2 and AIFonic Labs explain how young technology professionals can make successful career transitions into Data Science, AI/ML and Data Analytics while explaining their own inspiring career transition journeys into emerging technologies. They also share what opportunities are available, especially for women, in AI, Machine Learning, Data Science and Analytics fields. Listen to them giving anecdote-led tips on how to crack the hot data job roles along with career advice for making the career transition of your dreams. Subscribe to our channel to get updates on the latest videos.

Complete Machine Learning Course Machine Learning Tutorial for Beginners Edureka


It will provide you with the in-depth knowledge of the different types of Machine Learning with the different algorithms that lie under each category with a demo for each algorithm and the approach one should take to solve these problems. This video will be covering the following topics: 1:44 What is Data Science? Hit the subscribe button above: Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science.