Machine Learning with Python: Beginner's Guide to AI

Machine Learning with Python Basics (For Beginners)

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

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Last Updated: 2024-12-16 04:12:54 English Course Type: Self Learning

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

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.

Python Setup
Anaconda

Beginner in Machine Learning

Section 1 : Machine Learning with Python Basics 13 Lectures 00:16:01
Lecture 1 :
What is Machine Learning - Types of Machine Learning Preview
Lecture 2 :
Linear Regression With One Variable
Lecture 3 :
Linear Regression With One Variable (Cost Function - Gradient Descent)
Lecture 4 :
Linear Regression with Multiple Variable
Lecture 5 :
Logistic Regression (Classification)
Lecture 6 :
Logistic Regression (Cost Function - Gradient Descent)
Lecture 7 :
Logistic Regression (Multiclass)
Lecture 8 :
Regularization Overfitting
Lecture 9 :
Regularization (Linear and Logistic Regression)
Lecture 10 :
Neural Network Overview
Lecture 11 :
Neural Network (Cost Function)
Lecture 12 :
Advice for Applying Machine Leaning
Lecture 13 :
Unsupervised Machine Learning
Section 2 : Machine Learning Projects 3 Lectures 00:02:05
Lecture 1 :
Anaconda Setup
Lecture 2 :
Machine Learning Project 1
Lecture 3 :
Machine Learning Project 2
Section 3 : Python Basics 31 Lectures 01:08:20
Lecture 1 :
How to print
Lecture 2 :
Variables
Lecture 3 :
Receive Input from User
Lecture 4 :
Type Conversion
Lecture 5 :
String
Lecture 6 :
Formatted String
Lecture 7 :
String Methods
Lecture 8 :
Arithmetic Operations
Lecture 9 :
Math Functions
Lecture 10 :
If Statement
Lecture 11 :
If Statement Another Example
Lecture 12 :
Logical Operators
Lecture 13 :
Comparison Operators
Lecture 14 :
While
Lecture 15 :
For Loops
Lecture 16 :
Nested Loops
Lecture 17 :
List
Lecture 18 :
2D List
Lecture 19 :
List Methods
Lecture 20 :
Tuples
Lecture 21 :
Unpacking
Lecture 22 :
Dictionaries
Lecture 23 :
Functions
Lecture 24 :
Parameters
Lecture 25 :
Keyword Arguments
Lecture 26 :
Return Statement
Lecture 27 :
Try - Except
Lecture 28 :
Comments
Lecture 29 :
Classes
Lecture 30 :
General Review 1
Lecture 31 :
General Review 2
Section 4 : Python Projects 3 Lectures 00:19:51
Lecture 1 :
Python & PyCharm Setup
Lecture 2 :
Quiz Game
Lecture 3 :
Guessing Game

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Mohamed Gamal,

9916 Course Views

7 Courses

Have strong experience as CAD CAM Instructor: NX (CAD - CAM - CAE -Mold Wizard - CNC Post Builder, Sheet Metal) Solid Works, Inventor, Solid Edge Have strong experience in post processing for CNC machines (Milling, Turning, Wire EDM) Making a (G code) programs for a lot of mechanical products and manufacturing it in CNC machines (Milling 3 Axis, Multi Axis). Have strong knowledge of mold wizard of NX (Injection Mold Plastic ) Making a complete mold base for plastic parts and get the drawings for the manufacturing.