Machine Learning Steps | What Is Machine Learning | Machine Learning Training | Edureka

🔥Machine Learning Training with Python: https://www.edureka.co/machine....-learning-certificat
This Edureka video on Machine Learning Steps will help you understand, what are the various steps involved in while developing a Machine Learning Model. By the end of this video you will be able to implement a Machine Learning Pipeline. These are the following topics that are covered in this Machine Learning Steps video:
00:00:00 Introduction
00:00:47 Why Machine Learning?
00:02:04 What is Machine Learning?
00:04:36 Machine Learning PipeLine
00:08:51Demo: Implement a Machine Learning Pipeline

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How it Works?
1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate!
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About the Course :

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.
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Why Learn Machine Learning with Python?
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. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
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