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Beginner Certification in Machine Learning


 Beginner

INR 5000/-  INR 999/-

What You'll Learn

Make powerful analysis
Make robust Machine Learning models
Create strong added value to your business
Build an army of powerful Machine Learning models
Making accurate predictions

About

Machine learning is the science of getting computers to act without being explicitly programmed.Many researchers also think it is the best way to make progress towards human-level AI. Machine Learning is everywhere; if you want to know how companies like Google and Amazon extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

In this program, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques. course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control),autonomous vehicles, text understanding, computer vision, medical informatics, database mining, and other areas.

Requirements

  • No coding experience is necessary
  • Any operating system can be used like Mac,Windows and linux

Course Outline

  • What is Machine Learning
  • Install Python and Anaconda
  • Installing packages: numpy, pandas, matplotlib, sklearn
  • Introduction to Python
  • Flow Control (If, for, while) Statements
  • Data Structures - Numbers, Lists, Tuples, Dictionary, Strings
  • Functions and classes in Python
  • Ndarray Object
  • Data Types in Numpy
  • Array Attributes and Manipulation in Numpy
  • Indexing & Slicing
  • Regression
  • Simple Linear Regression
  • Multiple Linear Regression
  • Support Vector Regression
  • Decision Tree Regression
  • Random Forest Regression
  • Classification
  • Support Vector Classification(SVM)
  • K - Nearest Neighbour Algorithm(KNN)
  • Naive Bayes Classification
  • Decision Tree Classification
  • Random forest Classification
  • Clustering
  • K-means Clustering Algorithm
  • Hierarchical clustering

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Student feedback

★★★★★
4.5 average based on 2 reviews
Vikas Verma
★★★★★ 3 months ago

Good

Ashutosh Mishra
★★★★ 3 months ago

Better in Corona pandemic , good to see this type of effort in learning.

Course Features

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