Machine Learning with Python Basics (For Beginners)

About Machine Learning with Python Basics (For Beginners)

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

Notes:

You will Learn the basics of Machine Learning.

You will learn the basics of python.

You will need to setup Anaconda.

You will need to setup python & PyCharm

This course is considered as first step for the Machine Learning.

You can ask anytime.

No Programming Experience Needed for this course.

Python for Data Science and Machine Learning is a great course that you can take to learn the implementation of ML models in Python.

This course considered as step one in the Machine Leaning, You will learn the concept of the Machine Learning with python basics.