Machine Learning
4.4
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Course Instructor
INTRNFORTE
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Course Overview
Course Curriculum
1 Subject
Machine Learning
4 Exercises • 57 Learning Materials
Important Guidelines!
Important Guidelines Before you start
ML Introduction
Introduction
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IPYNB FILES OF ALL LESSON
Numphy Briefly
Numphy Briefly
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Assignment
Pandas Briefly
Pandas Briefly
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Assignment
Stats
Stats
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Assignment
Probability Basic
Probability Basic
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Data Wrangling
Data Wrangling
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Assignment
Data visualization
Data visualization
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Assignment
Handling null
Handling null
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Assignment 1
Assignment 2
Quiz 1
Exercise
Imputing and encoding
Imputing and encoding
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Types of modeling
Types of modeling
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Linear regression
Linear regression
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Logistic regression
Logistic regression
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Quiz 2
Exercise
General modeling technique
General modeling technique
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K Nearest Neighbour
K Nearest Neighbour
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Decision tree
Decision tree
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Quiz 3
Exercise
Ensemble technique
Ensemble Technique
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Cross-validation and Hyperparameter tuning
Cross-validation and Hyperparameter tuning
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K means clustering
Kmeans clustering
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Quiz 4
Exercise
Anomaly detection
Anomaly detection
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H clustering
Anomaly detection
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NLP Basics
NLP Basics
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Training Projects
Training Project 1
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Training Project 2
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Training Project 3
Spam Detection Engine Project
Project
Project to be given Format
Project
Project 2
Internship Training Certificate
Post Completion
Resume Building
Resume Building
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Placement Training
Career Planning & Mapping
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Corporate Culture Part 1
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Corporate Culture Part 2
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Critical Thinking 1
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Critical Thinking for Problem Solving 2
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Goal Setting
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Interview Skills
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LinkedIn Profile
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Placement Training 5 Personality
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Placement Training Modules 1 4
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Time Management
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Communication Skills Module 1
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Confidence Building
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Corporate Business Etiquette
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Group Discussion
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Interview Questions
Live Recordings
Recorded Video 1
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Recorded Video 2
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Free Job Simulation by MNC'S
Steps to Follow
Course Instructor
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INTRNFORTE
31 Courses • 18127 Students
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