Machine Learning with Python Basics (For Beginners)

🎓 Machine Learning with Python Basics (For Beginners)

Course Headline

🚀 You will Learn the Basics of Machine Learning with Python Step by Step (First Step For Beginners)! 🚀

Description

Embark on a journey to unlock the mysteries of Machine Learning and Python, tailored for beginners. This comprehensive course is designed to guide you through each fundamental step of machine learning using the versatile and powerful Python programming language. Whether you're a complete novice or looking to solidify your understanding, this course will provide you with the tools and knowledge to start your journey in data science and predictive analytics.

Steps of Machine Learning You Will Learn:

• 🚀 Import Data - Begin by understanding how to bring your data into a usable format.
• 🔄 Split Data into Training & Test - Master the art of separating your dataset for effective training and testing.
• 🏗️ Create a Model - Learn to build the initial structure of your machine learning model.
• ⚗️ Train The Model - Watch as your model learns from data, becoming more accurate over time.
• 🔍 Make Predictions - Apply what you've learned to make predictions on new data.
• ✅ Evaluate and Improve - Learn techniques for evaluating your model and improving its performance.

Machine Learning Course Contents:

1. What is Machine Learning - Types of Machine Learning (Supervised & Unsupervised)
2. Linear Regression with One Variable
3. Linear Regression with One Variable (Cost Function - Gradient Descent)
4. Linear Regression with Multiple Variables
5. Logistic Regression (Classification)
6. Logistic Regression (Cost Function - Gradient Descent)
7. Logistic Regression (Multiclass)
8. Regularization Overfitting
9. Regularization (Linear and Logistic Regression)
10. Neural Network Overview
11. Neural Network (Cost Function)
12. Advice for Applying Machine Learning
13. Machine Learning Project 1 - Apply your skills to a real-world problem.
14. Machine Learning Project 2 - Another hands-on project to consolidate your learning.

Python Basics Course Contents:

1. How to print - Your first step into Python programming.
2. Variables - Understand how to store and manipulate data.
3. Receive Input from User - Interact with the program's environment.
4. Type Conversion - Learn to change data types dynamically.
5. String - Master string operations and management.
6. Formatted String - Format your strings for clearer and more effective communication.
7. String Methods - Utilize built-in methods to enhance your string manipulation skills.
8. Arithmetic Operations - Perform calculations and understand operators.
9. Math Functions - Access and utilize mathematical functions.
10. If Statement - Make decisions within your code.
11. Logical Operators - Combine conditions for more complex decision-making.
12. Comparison Operators - Compare values and understand equality in Python.
13. While - Execute code repeatedly based on a condition.
14. For Loops - Perform operations multiple times, with ease.
15. Nested Loops - Combine loops to handle more complex scenarios.
16. List - Learn to store multiple items in one variable.
17. 2D List - Work with lists of lists for complex data organization.
18. List Methods - Manipulate and understand list operations and capabilities.
19. Tuples - Understand the immutable counterpart to lists.
20. Unpacking - Simplify your code by unpacking tuples or lists.
21. Dictionaries - Store data in a key-value pair format, making it easy to retrieve data.
22. Functions - Write reusable blocks of code to perform specific tasks.
23. Parameters & Keyword Arguments - Pass data into functions for versatile functionality.
24. Return Statement - Output values from your functions.
25. Tricks & Tips - Learn best practices and efficient ways to write Python code.

Additional Notes:

• Before starting, ensure you have a basic understanding of programming concepts and some familiarity with the Python language.
• This course requires installation of Python and related libraries for machine learning (e.g., TensorFlow, scikit-learn).
• You will work on two comprehensive projects to apply your knowledge and enhance your practical skills.
• This is the first step in a journey that could lead to specializations within data science, machine learning, or even artificial intelligence.

What You'll Gain:

• A solid foundation in both Python programming and machine learning principles.
• The ability to approach complex problems with logic and code.
• Hands-on experience through practical projects.
• Confidence in using Python for data analysis and machine learning tasks.
• A clear understanding of the steps involved in creating a machine learning model from scratch.

Join us on this exciting learning adventure and unlock your potential as a developer in the field of artificial intelligence and machine learning with Python! 🤖💻🚀