What you'll learn

The course provides path to start career in Data Analysis and Data Science

Problem Solving Approach

Impress interviewers by showing an understanding of the Data Analysis withMachine Learning Algorithm concept

Python Basic to Advance Concept with Numpy, Pandas, Matplotlib, Seaborn, Plotly Library

Scikit Learn Library in Depth

Data Analysis with Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest

Machine Learning Types Such as Supervise Learning, Unsupervised Learning

Data Analysis Case Study

Requirements

It start with Basics

Only a passion for Learning

All software used in this course is either available for Free or as a Demo version

This course is intended for absolute bners in programming

Description
Data Analysis with Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered.

The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.

Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.

Who this course is for:

The course is ideal for bners, as it starts from the fundamentals and gradually builds up your skills in Data Analysis

People interested to learn Data Analysis with Machine Learning Algorithms using Scikit Learning Library and Python



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