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Complete Machine Learning Course
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This Complete Machine Learning Course course on LearnVern is completely free. It will provide a comprehensive understanding of the topic and its practical applications.
Free Course
#1
See all ranking
Complete Machine Learning Course
by
Learnvern
This Complete Machine Learning Course course on LearnVern is completely free. It will provide a comprehensive understanding of the topic and its practical applications.
Free Course
#1
See all ranking
2 Modules
with Certifications
2+ Hours
of Recorded Content
4.4 Rated
by 10000 Learners
English
Language
2 Modules
with Certifications
2 + Hours
of Recorded Content
4.4 Rated
by 10000Learners
Read all Reviews
English
Language
Key Features:
This course is completely Free
100% online and Self-paced learning
Available in Multiple languages
Access on Mobile and TV
Full lifetime access to all content
Downloadable Resources
-
Getting Started
Getting Started with Machine Learning
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Introduction
- Introduction to Machine Learning
- Environment Setup Part 1
- Environment Setup Part 2
- Environment Setup Part 3
- Quiz : Introduction to Machine Learning
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Data Preprocessing for Machine Learning
- Data Wrangling in Machine Learning
- Importing Libraries and Dataset in Machine Learning
- Handling Missing Data in Machine Learning
- Handling Missing Data in Machine Learning - Practical
- Encoding Categorical Data in Machine Learning
- Encoding Categorical Data in Machine Learning - Practical
- Splitting Dataset in Machine Learning
- Splitting Dataset in Machine Learning - Practical
- Normalizing the Data in Machine Learning - Part 1
- Normalizing the Data in Machine Learning - Part 2
- Finding Machine Learning Datasets
- Exploratory Data Analysis in Machine Learning
- Plotting Graphs in Machine Learning - Part 1
- Plotting Graphs in Machine Learning - Part 2
- Distribution Models in Machine Learning - Part 1
- Distribution Models in Machine Learning - Part 2
- Assignment : Data Preprocessing for Machine Learning
- Quiz : Data Preprocessing for Machine Learning
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Machine Learning Paradigms
- Machine Learning Paradigms
- Assignment : Machine Learning Paradigms
- Quiz : Machine Learning Paradigms
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Supervised Learning Algorithms
- Overview of Classification
- Logistic Regression in Machine Learning
- Logistic Regression in Machine Learning - Practical - 1
- Logistic Regression in Machine Learning - Practical - 2
- KNN in Machine Learning
- KNN in Machine Learning Practical - 1
- KNN in Machine Learning - Practical 2
- Decision Trees for Classification in Machine Learning
- Decision Trees for Classification in Machine Learning - Practical - 1
- Decision Trees for Classification in Machine Learning - Practical - 2
- Decision Tree Iterative Dichotomiser in Machine Learning - 3
- Random Forest in Machine Learning
- Support Vector Machine Classifier
- Support Vector Machine Classifier - Practical - 1
- Support Vector Machine Classifier - Practical - 2
- Naive Bayes Classifier in Machine Learning
- Naive Bayes Classifier in Machine Learning Practical - 1
- Naive Bayes Classifier in Machine Learning Practical - 2
- Evaluating Classification Models Performance in Machine Learning
- Evaluating Classification Models Performance in Machine Learning Practical
- Assignment : Supervised Learning Algorithms
- Quiz : Supervised Learning Algorithms
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Regression Algorithms
- Simple Linear Regression in Machine Learning
- Simple Linear Regression in Machine Learning - Practical
- Salary Prediction using Linear Regression in Machine Learning
- Multi-Linear Regression in Machine Learning
- Startup Prediction using Multiple Regression in Machine Learning
- Support Vector Regressor in Machine Learning
- Support Vector Regressor in Machine Learning - Practical - 1
- Support Vector Regressor in Machine Learning Practical - 2
- Decision Tree Regressor in Machine Learning
- Decision Tree Regressor in Machine Learning Practical - 1
- Decision Tree Regressor in Machine Learning Practical - 2
- Regressor Model Selection in Machine Learning
- Evaluating Regression Model Performance in Machine Learning
- Evaluating Regression Model Performance in Machine Learning - Practical
- Assignment : Regression Algorithms
- Quiz : Regression Algorithms
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Unsupervised Learning Algorithms
- Distance Metrics in Machine Learning
- K-Means Clustering in Machine Learning
- K-Means Clustering in Machine Learning - Practical
- Mall Customers Prediction using K Means Clustering in Machine Learning
- Hierarchical Clustering in Machine Learning - Agglomerative , Divisive
- Agglomerative Clustering in Machine Learning - Practical
- Divisive Clustering in Machine Learning - Practical
- DBscan Spatial Clustering in Machine Learning
- Mall Customers Prediction using Hierarchical Clustering in Machine Learning
- Assignment : Unsupervised Learning Algorithms
- Quiz : Unsupervised Learning Algorithms
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Association Rule Mining
- Association Rule in Machine Learning - Apriori, FP Growth
- Association Rule in Machine Learning - Apriori Practical
- Market Basket Analysis using Apriori in Machine Learning
- FP Growth in Machine Learning
- Market Basket Analysis using FP Growth in Machine Learning
- Assignment : Association Rule Mining
- Quiz : Association Rule Mining
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Reinforcement Learning
- Reinforcement Learning in Machine Learning - Multi Armed Bandits
- Upper Confidence Bound in Machine Learning - Practical
- Thompson Sampling in Machine Learning - Practical
- Q Learning in Machine Learning
- Assignment : Reinforcement Learning
- Quiz : Reinforcement Learning
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Dimensionality Reduction
- Overview of Dimensionality Reduction in Machine Learning
- Principal Component Analysis in Machine Learning
- Principal Component Analysis in Machine Learning - Practical
- Linear Discriminant Analysis in Machine Learning
- Linear Discriminant Analysis in Machine Learning - Practical
- Assignment : Dimensionality Reduction
- Quiz : Dimensionality Reduction
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Regularization and Optimization
- Basics of Regularization and Optimization in Machine Learning
- Cross Validation in Machine Learning
- Hyperparameter Tuning in Machine Learning
- Sampling Methods in Machine Learning
- Underfitting and Overfitting in Models in Machine Learning
- Variance and Bias in Machine Learning
- Assignment : Regularization and Optimization
- Quiz : Regularization and Optimization
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Advance Trends in Machine Learning
Advance Trends in Machine Learning
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Introduction to Keras
- Introduction to Keras and Deep Learning
- Practical Demonstration -Keras
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Projects
- Reinforcement Learning Project - Teach a Taxi Part 1
- Reinforcement Learning Project - Teach a Taxi Part 2
- Reinforcement Learning Project - Teach a Taxi Part 3
- Reinforcement Learning Project - Teach a Taxi Part 4
- Loan Prediction Project Part 1
- Loan Prediction Project Part 2
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Course Summary
Course Summary
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Interview Question
- Interview Questions Part 1
- Interview Questions Part 2
- Interview Questions Part 3
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Career Guideline
Career Guideline
Course Offerings
Certificate you will get
NSDC Certificate of Partnership with LearnVern.
Help build strong resume.
Great add-on to get Internship.
Upgrade your Job with this certificate proof.
Pre Requsites
Basic proficiency in reading and writing.
Familiarity with using technology for research and assignments.
A curious mind and willingness to participate actively.
Course is for
Freshers
Professionals
Students
FAQ's
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Can LearnVern help understand what is machine learning?Yes, we have a module fully dedicated to advanced trends in Machine Learning. Learn about ML and its latest trends that help you stay abreast with the latest industry knowledge.
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What are the skills required to learn Machine Learning from scratch?Skills required for ML include regression, linear equations, basic calculus, graph distribution methods, probability, basic statistics formulas, and programming knowledge To pursue an ML course, you must have opted for Mathematics and Statistics for a Bachelor's degree course. Programming basic learners, software engineers and research students can also opt for this program.
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What all is offered in the Machine Learning tutorial from LearnVern?The tutorial offers a comprehensive insight into the core concepts of ML including the introduction to ML, ML and AI basics, applications and ML trends and updates, divergent ML tools and environment setup.
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Can I do LearnVern’s Machine Learning Course with my current job?Yes, LearnVern’s Machine Learning Course is self-paced and offers complete offline study material support to the enrollers. Thus, you can pursue it as per your schedule.
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Is LearnVern’s Machine Learning Course available in Hindi or other native languages?Yes, the USP of our Machine Learning course is its availability in Hindi and other easily understandable native languages. Thus, you would have better clarity and learn with ease in the language of your choice
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