Understanding Machine Learning for Data Science in python. Best skill to get in free time.
What you will learn
What is basically Machine Learning? How Machine Learns?
Learn the most Basic Mathematics behind Simple Linear Regression and its Best fit line.
What is Gradient Descent, how it works Internally with full Mathematical explanation.
Why take this course?
**π Course Headline:**
Unlock the Power of Data Science: Master **Machine Learning for Python** from Scratch!
**π Course Description:**
Dive into the fascinating world of **Machine Learning** and gain a solid understanding of its core principles with our comprehensive online course. Tailored for beginners, this course is your gateway to mastering Data Science using Python, the language that’s shaping the future of technology.
π **Why Choose This Course?**
– **No Prior Knowledge Required:** Whether you’re a student, professional, or an enthusiast, this course is designed for anyone with a passion to learn Machine Learning from scratch.
– **Complete Machine Learning Basics:** We start with the fundamentals, ensuring you build a strong foundation before moving on to more complex concepts.
– **In-Depth Mathematical Insights:** Get ready to explore detailed mathematical explanations behind Cost functions and the practical application of Gradient Descent in Simple Linear Regression.
– **Real-World Application:** While we won’t cover extensive coding, code examples are provided in the resources to help you grasp the concepts better.
**π Key Takeaways:**
– **Understanding Machine Learning Concepts:** Learn what Machine Learning is and its importance in today’s data-driven world.
– **Simple Linear Regression Explained:** Unpack the concept of Simple Linear Regression with clear, step-by-step guidance.
– **Mathematical Foundations:** Grasp the essential mathematical concepts that underpin Machine Learning algorithms.
– **Cost Function & Gradient Descent:** Understand how to minimize errors in predictions with Cost functions and optimize parameters using Gradient Descent.
**π Course Structure:**
1. **Introduction to Machine Learning:** An overview of the field, its applications, and what you can achieve with Machine Learning.
2. **Machine Learning Concepts:** A breakdown of key concepts that form the basis of Machine Learning algorithms.
3. **Simple Linear Regression (SLR):** A detailed exploration of SLR, including its assumptions, how it works, and why it’s a critical starting point for any Machine Learning journey.
4. **Cost Functions:** An in-depth look at the mathematical functions used to measure the difference between predicted values and actual values.
5. **Gradient Descent:** Learn about this optimization algorithm used to minimize cost functions in the context of SLR.
6. **Practical Applications & Code Examples:** Real-world scenarios and Python code snippets that bring theoretical concepts to life.
**π Learning Outcomes:**
By the end of this course, you will have a comprehensive understanding of Machine Learning fundamentals with a focus on Python programming. You’ll be equipped with the knowledge to apply these principles to real-world data science challenges and set the stage for advanced Machine Learning studies.
**π
Start Your Learning Journey Today!**
Embark on your journey towards mastering Machine Learning with Python. Enroll in “Machine Learning Fundamentals [Python]” with Rishi Bansal and transform your skills, your career, or simply satisfy your curiosity about one of the most exciting fields in technology today.
—
Join us and turn your free time into valuable skills that will open doors to a world of possibilities! πππ‘