Machine Learning With Python Basics (For Beginners)

Learn the Basics of Machine Learning with Python (First Step For Beginners)

What you'll learn
You Will learn basic concept of Machine Learning, Types of Machine Learning
You Will learn basic concept of Linear Regression With One Variable & Multiple
You Will learn basic concept of Logistic Regression
You Will learn basic concept of Regularization (Linear and Logistic Regression)
You Will learn basic concept of Neural Network
Machine Learning Projects
Requirements
No Programming Experience Needed
Description
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 1Machine Learning Project 2Python Basics Course Contents:How to printVariablesReceive Input from UserType ConversionStringFormatted StringString MethodsArithmetic OperationsMath FunctionsIf StatementLogical OperatorsComparison OperatorsWhileFor LoopsNested LoopsList2D ListList MethodsTuplesUnpackingDictionariesFunctionsParametersKeyword ArgumentsReturn StatementTry - ExceptCommentsClassesNotes: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 & PyCharmThis 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.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Machine Learning with Python Basics

Lecture 2 What is Machine Learning - Types of Machine Learning

Lecture 3 Linear Regression With One Variable

Lecture 4 Linear Regression With One Variable (Cost Function - Gradient Descent)

Lecture 5 Linear Regression With Multible Variable

Lecture 6 Logistic Regression (Classification)

Lecture 7 Logistic Regression (Cost Function - Gradient Descent)

Lecture 8 Logistic Regression (Multiclass)

Lecture 9 Regularization Overfitting

Lecture 10 Regularization (Linear and Logistic Regression)

Lecture 11 Neural Network Overview

Lecture 12 Neural Network (Cost Function)

Lecture 13 Advice for Applying Machine Leaning

Section 3: Machine Learning Projects

Lecture 14 Anaconda Setup

Lecture 15 Machine Learning Project 1

Lecture 16 Machine Learning Project 2

Section 4: Python Basics

Lecture 17 How to print

Lecture 18 Variables

Lecture 19 Receive Input from User

Lecture 20 Type Conversion

Lecture 21 String

Lecture 22 Formatted String

Lecture 23 String Methods

Lecture 24 Arithmetic Operations

Lecture 25 Math Functions

Lecture 26 If Statement

Lecture 27 If Statement Another Example

Lecture 28 Logical Operators

Lecture 29 Comparison Operators

Lecture 30 While

Lecture 31 For Loops

Lecture 32 Nested Loops

Lecture 33 List

Lecture 34 2D List

Lecture 35 List Methods

Lecture 36 Tuples

Lecture 37 Unpacking

Lecture 38 Dictionaries

Lecture 39 Functions

Lecture 40 Parameters

Lecture 41 Keyword Arguments

Lecture 42 Return Statement

Lecture 43 Try - Except

Lecture 44 Comments

Lecture 45 Classes

Lecture 46 General Review 1

Lecture 47 General Review 2

Section 5: Python Projects

Lecture 48 Python & PyCharm Setup

Lecture 49 Quiz Game

Lecture 50 Guessing Game

Beginner in Machine Learning