Email: online@course.in
Main Road
MACHINE LEARNING REGRESSION MASTERCLASS IN PYTHON
Python and Machine Learning Online Institute
Technology Learners
Regular Offline and Online Live Training
Week Days and Week Ends
60 Days
•How to work with Python and Machine Learning Tool.
•Python and Machine Learning Script How to apply and use it.
•Learn To Create Python and Machine Learning Programs The Easy Way
•How to perform read and write operations in Python and Machine Learning.
•Learn from scratch how to execute code with Python and Machine Learning
•Become a Python and Machine Learning Certified Developer! Learn all Python and Machine Learning Developer topics
•Learn and Understand Python and Machine Learning From a total Beginner to and Expert
•Understand Python and Machine Learning and how to use to build web applications on to Python and Machine Learning.
•with this time saving course you will Learn Python and Machine Learning and ready to use it
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•Additional Sessions for Doubt Clearing
•Course has been framed by Industry experts
•Flexible batch timings – Weekend & weekdays.
•Classes are Accessible on Website and Mobile Apps
• Greater productivity and increased workforce morale
•Repeating of lectures allowed (based on seat availability)
•Curriculum based on course outlines defined by in-demand skills in Python.
•We help the students in building the resume boost their knowledge by providing useful Interview tips
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•.Net, Asp.net, C#, Angular, React, .Net Developer, Ui, Ui Development, Single Page Application, Sql, Product Development
•Core Java, java, python, php, plsql, Ios Development, Android Development, Software Development, Software Testing, hadoop, cloud, devops, Technical Support
•JSF, hibernate, spring, Java SE 6 Developer, Sun Certified Developer for Java 2 Platform / Oracle Certified Master, html
•Sap, Process Executive, Hadoop Developer, Hadoop Architect, Sap Srm/snc Testing, Sap Pp / Qm Testing, Sap Ewm Testing, Sharepoint Developer, T24 Technical And
•Solution Architect, Technical Lead, Software Developer, Testing Engineer, Project Manager, sap, sas, sql, magento, wordpress, laravel, mysql, Payment Gateways
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INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]
•Course Welcome Message
•Updates on Reviews
•Course Overview
•BONUS: Learning Path
•ML vs. DL vs. AI
•ANACONDA AND JUPYTER INSTALLATION
•Download and Set up Anaconda
•What is Jupiter Notebook
•SIMPLE LINEAR REGRESSION
•Intro to Simple Linear Regression
•Simple Linear Regression Intuition
•Least Squares
•Project #1 – Overview
•Project #1 – Data Visualization
•Project #1 – Divide Data into Training and Testing
•Project #1 – Train Model
•Project #1 – Test Model
•Project #2 – Overview
•Project #2 – Solution
•Project #2 – Visualization
•Project #2 – Prepare Training and Testing Data
•Project #2 – Test Model
•Project #2 – Model Testing
•REGRESSION KEY PERFORMANCE INDICATORS
•Regression Metrics Intro
•Regression Metric Part 1
•Regression Metric Part 2
•Bias Variance Tradeoff
•POLYNOMIAL REGRESSION
•Polynomial Regression Intro
•Polynomial Regression – Intuition
•Poly Regression – Salary Load Data
•Poly Regression – Visualize Data
•Poly Regression – Linear Trainingtesting
•Poly Regression – Poly Part 1
•Poly Regression – Poly Part 2
•Poly Regression Project 2 Overview
•Poly Regression – Economies Linear -1
•Poly Regression – Economies Linear -2
•Poly Regression – Economies Poly
•MULTIPLE LINEAR REGRESSION
•Multiple Linear Regression Intro
•Multiple Linear Regression Overview
•Project #1 – Load Data and Libraries
•Project #1 – Model Training and Evaluation
•Project #1 – Model Results Evaluation
•Project #2 – Load Data
•Project #2 – Data Visualization
•Project #2 – Train the Model
•Project #2 – Model Evaluation
•Project #2 – Retraining Model
•LOGISTIC REGRESSION
•Logistic Regression Intro
•Logistic Regression Intuition
•Confusion Matrix
•Project #2 – Data Import
•Project #2 – Data Cleaning
•Project #2 – Training Testing
•Model Testing Visualization
•APPLY ARTIFICIAL NEURAL NETWORKS TO PERFORM REGRESSION TASKS
•Artificial Neural Networks Intro
•Theory Part 1
•Theory Part 2
•Theory Part 3
•Theory Part 4
•Theory Part 5
•Theory Part 6
•Project – Load Dataset
•Project – Visualize Dataset
•Scale the Data
•Train the Model
•Evaluate the Model
•Model Improvement with more features
•LASSO AND RIDGE REGRESSION
•Ridge and Lasso Intro
•Ridge Lasso Part 1
•Ridge Lasso Part 2
•Ridge Lasso Part 3
•Ridge and Lasso in Practice
•***YOUR SPECIAL BONUS***
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