No of Team Members | 5 | 4 | 3 | 2 | 1 |
---|---|---|---|---|---|
Price per student | ₹ 5999 ₹ 5599 | ₹ 6249 ₹ 5749 | ₹ 6665 ₹ 5999 | ₹ 7499 ₹ 6499 | ₹ 9999 ₹ 7999 |
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This career building course involves you to build multiple projects and helps you develop a good understanding of Machine Learning practically.
You will develop the following projects from basics to advanced:
Login to our Online Learning Portal will be provided instantaneously upon enrolling. This Portal gives you access to video lectures, tutorials and quizzes required to develop your Machine Learning using Python project. As you complete the course your project will also be completed.
Module 1: What is Machine Learning
Learn: What is Machine Learning
Learn: Supervised vs Unsupervised Learning
Learn: Machine Learning Terminology & Pipeline
Learn: Tools for Machine Learning
Do: Installation of Anaconda
Do: Setting up a Jupyter Notebook
Do: Explore Jupyter
Review: What is Machine Learning
Module 2: Your First Machine Learning Model - Boston Housing
Learn: Boston Housing - Problem Description
Learn: Types of Data & Its Implications
Learn: Preprocessing of Data
Do: Import BH Data
Do: Data Visualization of BH Data
Do: Correlation between Target & Attributes
Review: Your First Machine Learning Model!
Module 3: Mean Squared Error
Learn: Errors & Types
Learn: Mean Squared Error
Do: Define MSE Function
Do: Calculate MSE for Sample Data
Review: Mean Squared Error
Module 4: Data Splitting & Accuracy of Model - Boston Housing
Learn: Testing & Training Data - Cross Validation
Do: Split the dataset
Review: Data Splitting & Accuracy of Model
Module 5: Linear Regression - Boston Housing
Learn: Linear Regression & its Types
Learn: Gradient Descent - Learning Rates
Learn: Programming logic - Update Function
Do: Update Function
Learn: Programming logic - Descent Function
Do: Descent Function
Learn: Programming logic - Model Training Visualization
Do: Model Training Visualization
Learn: Programming logic - Error Visualization
Do: Error Visualization
Review: Linear Regression
Module 6: Machine Learning Prediction - Boston Housing
Learn: Prediction & Validation
Learn: Programming logic - Prediction of Prices
Do: Prediction of Prices
Do: Train Model with Different Attributes & Predict
Review: Machine Learning Prediction
Module 7: Machine Learning Prediction - Boston Housing
Learn: Credit Card Fraud Detection - Problem Description
Learn: Data Preprocessing - Programming Logic
Do: Import & Visualize Data
Do: Preprocess Data
Module 8: SelectKBest Features
Learn: What is SelectkBest
Learn: SelectKBest - Programming Logic
Do: SelectKBest Features
Do: Discard Bad Features
Do: Visualize Features
Module 9: Train Model
Learn: What is Gaussian Naive Bayes Algorithm
Learn: What is Cross Validation
Learn: Gaussian Naive Bayes - Programming Logic
Do: Split Dataset
Module 10: Fraud Prediction
Learn: What is Confusion Matrix
Learn: Confusion Matrix - Programming Logic
Learn: Evaluation & Visualization
Module 11: Movie Recommendation System
Learn: Movie Recommendation - Problem Description
Learn: MRS - Problem Setup
Do: Download & Import Data
Module 12: MRS - Data Preprocessing
Learn: MRS - Data Visualization - Programming Logic
Learn: MRS - Data Processing - Programming Logic
Do: MRS - Data Vizualization - Movies
Do: MRS - Data Processing - Movies
Do: MRS - Data Vizualization & Processing - Users
Do: MRS - Create pivot table and sparse matrix
Do: MRS - Map Data - Movies to Movie ID
Module 13: MRS - Train the Model
Learn: K Nearest Neighbours
Do: MRS - Train the Model
Review: K Nearest Neighbours
Module 14: MRS - Evaluate Model & Predict
Learn: MRS - Search Movie Title - Programming Logic
Do: MRS - Search Movie Title
Do: MRS - Recommend Movies
Module 15: Recognize Handwritten Digits
Learn: What is Deep Learning?
Learn: Recognize Handwritten Digits - Problem Description
Learn: MNIST Dataset - Description
Learn: Recognize Handwritten Digits - Problem Setup
Do: Import MNIST Dataset
Module 16: MNIST Dataset - Preprocessing the Data
Learn: Basic Properties of an Image
Do: MNIST Data - Properties of the Dataset
Do: MNIST Data - Visualize Samples of the Data
Do: MNIST Data - Scaling the Data
Module 17: Neural Networks in Deep Learning
Learn: What is a Neural Network
Learn: Representation of Neural Networks
Learn: Output of a Neural Network
Learn: Activation Functions in Neural Networks
Learn: TensorFlow & Keras - Basic Concepts
Learn: Recognize Handwritten Digits - Deep Learning Model - Programming Logic
Do: Recognize Handwritten Digits - Setup Neural Network
Do: Recognize Handwritten Digits - Train the Model
Module 18: Recognize Handwritten Digits - Evaluate the Model & Predict the Digits
Learn: Recognize Handwritten Digits - Model Evaluation - Programming Logic
Do: Recognize Handwritten Digits - Vizualize model training
Do: Recognize Handwritten Digits - Evaluate Accuracy & Make Predictions
Do: Recognize Handwritten Digits - Evaluate Accuracy & Make Predictions
Do: Recognize Handwritten Digits - Function to Visualize Results
Do: Recognize Handwritten Digits - Visualize Prediction of Random Samples
Do: Recognize Handwritten Digits - Visualize Prediction of Incorrect Samples
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Anybody who want to develop machine learning skills & build an exciting career in machine learning can take up this career building course.