Machine Learning Course in India (100% Job oriented)

1.1 Understanding the fundamentals of machine learning

1.2 Overview of different types of machine learning algorithms

1.3 Introduction to the machine learning workflow

2.1 Introduction to NumPy arrays

2.2 Basic array operations and manipulations

2.3 Handling multi-dimensional arrays for data storage and processing

3.1Introduction to Pandas Dataframe

3.2Data indexing and selection

3.3Data cleaning, transformation, and manipulation techniques

4.1 Overview of scikit-learn library

4.2 Introduction to supervised and unsupervised learning algorithms provided by scikit-learn

4.3Understanding scikit-Learn API and usage

5.1 Understanding regression algorithms for continuous target variables

5.2 Introduction to classification algorithms for categorical target variables

5.3 Hands-on implementation of regression and classification models using scikit-learn

6.1 Introduction to clustering algorithms for grouping similar data points

6.2Understanding different clustering techniques such as K-means, hierarchical clustering, and DBSCAN

6.3Implementing clustering algorithms using scikit-learn

7.1Overview of evaluation metrics for assessing model performance

7.2Techniques for cross-validation and train-test splitting

7.3Hands-on practice with model evaluation using scikit-learn

8.1 Introduction to model selection techniques such as grid search and random search

8.2 Understanding hyperparameters and their impact on model performance

8.3 Tuning hyperparameters to optimize model performance using scikit-learn

9.1 Techniques for feature engineering to extract meaningful information from raw data

9.2 Methods for feature selection to identify relevant features for model training

9.3 Implementing feature engineering and selection techniques using scikit-learn

10.1 Applying machine learning techniques to real-world datasets

10.2 Working on guided projects and case studies to reinforce learning

10.3 Solving data analysis and prediction tasks using machine learning algorithms