Steps of Machine Learning that you Will learn: Import the data. Split data into Training & Test. Create a Model. Train The Model. Make Predictions. Evaluate and improve. Machine Learning Course Contents: What is Machine Learning - Types of Machine Learning (Supervised & Unsupervised). Linear Regression with One Variable. Linear Regression with One Variable (Cost Function - Gradient Descent). Linear Regression with Multiple Variable. Logistic Regression (Classification). Logistic Regression (Cost Function - Gradient Descent). Logistic Regression (Multiclass). Regularization Overfitting. Regularization (Linear and Logistic Regression). Neural Network Overview. Neural Network (Cost Function). Advice for Applying Machine Leaning. Machine Learning Project 1 Machine Learning Project 2 Python Basics Course Contents: How to print Variables Receive Input from User Type Conversion String Formatted String String Methods Arithmetic Operations Math Functions If Statement Logical Operators Comparison Operators While For Loops Nested Loops List 2D List List Methods Tuples Unpacking Dictionaries Functions Parameters Keyword Arguments Return Statement Try - Except Comments Classes
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