pthon image

Machine Learning for Beginners

Instructor led best course for learning machine learning concepts and developing models using real world case studies.

Hurry up to get enroll.. ₹20,000 ₹10,000 50% OFF

4.7

Rating

35 Hrs

Duration

Beginner

Level

30

Assignments

What you'll learn

Descriptive and Inferential statistics in details with case studies
Regression and classification algorithms in details with case studies
End to end Machine learning model lifecycle in details
Factor analysis and Time series forecasting with case studies

Who should take this course

Anyone with mid-level python programming knowledge
Anyone interested in learning machine learning algorithms in details

Skills you'll gain

Descriptive statistics
Inferential statistics
Supervised learning
Unsupervised learning
Reinforcement learning
Regression
Classification
Clustering
Factor analysis
Time series forecasting

Course contents

Data Types
Sampling types
Central tendency
Measure of spread and position
Skewness

Sampling
Confidence Interval
Hypothesis testing
Comparison test
Correlation test

Supervised Learning
Unsupervised Learning
Semi supervised Learning
Reinforcement Learning

Problem Definition
Data selection
Exploratory data analysis
Data cleaning
Outlier analysis
Data transformation
Feature selection
Training the model
Model validation and performance metrics

Understanding the case study
Data preprocessing
Defining the hypothesis
Assumptions of Linear regression
Defining the cost function
Training the model using python sk-learn
Error analysis and performance metrics

Understanding the case study
Data preprocessing
Defining the hypothesis
Assumptions of Logistic regression
Defining the cost function
Training the model using python sk-learn
Error analysis and performance metrics

Understanding the case study
Data preprocessing
Defining the hypothesis
Assumptions of decision tree
Defining the cost function
Training the model using python sk-learn
Error analysis and performance metrics

Types and techniques

Understanding the case study
Data preprocessing
Defining the hypothesis
Assumptions of K-Means
Defining the cost function
Training the model using python sk-learn
Error analysis and performance metrics

Benefits of this technique
Assumptions of Hierarchical clustering
Defining the cost function
Implementation using python sk-learn
Output analysis and performance metrics

Understanding the case study
Benefits of PCA
Data preprocessing
Assumptions of PCA
Implementation using python sk-learn
Output analysis and performance metrics

Overview and Benefits
Keys concepts
Types and techniques

Understanding the case study
Assumptions of ARIMA
Parameter identification
Defining the cost function
Model fitting and forecasting using python sk-learn
Output analysis and performance metrics

Advanced Machine Learning

This course contains advanced ML concepts like ensemble modeling, Deep Learning, regularization, hyper parameter tuning and Reinforcement Learning.

NLP for Beginners

In this course text representation, POS tagging, feature extraction, preprocessing, sentiment analysis, text similarity and topic mining will be taught.

Road to Data Scientist

This Module allows user to create a digital twin for any document(e.g pdf, word).