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Machine learning refers to the process of enabling computer systems to learn with data using statistical techniques without being explicitly programmed. It is the process of active engagement with algorithms in order to enable them to learn from and make predictions on data.It is seen as a subset of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions.The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning.

Course Curriculum

Python Programming 1. Variables 2. Numbers 3. String 4. List 5. Tuples 6. Dictionary 7. Comparison Operators 8. Conditional Statements(if, else, elif) 9. Loops Statement(for loop, while loop) 10.Functions 11.Modules NumPy 1. Introduction 2. Installation 3. Understanding of Numpy 4. Create a one dimensional Array 5. Create a two dimensional Array 6. Create a three dimensional Array 7. Mathematical Operations with Numpy Pandas 1. About Pandas(Introduction) 2. Installation 3. Panda Series 4. Data Frame 5. Read And Write Files using Pandas Function 6. Handling Missing Values Matplot Lib 1. Introduction 2. Line Plot 3. Scatter Plot Real Time Project (Hands On) 1. How to import Library 2. Types of Data 3. How to load various types of Data 4. Exploratory Data Analysis 5. Data Visualisation 6. Data Cleaning 7. Data Splitting/How to Split Data 8. Introduction to ML Algorithms-Linear Regression 9. Prepare data for ML model 10.Model Selection and train 11.ML model testing 12.Calculate Accuracy of ML Model 13.Presentation of Project