Practical Machine Learning by Example in Python

🎉 Course Title: Practical Machine Learning by Example in Python 🤖💻

Course Headline:

A Deep Dive into Building Machine Learning and Deep Learning Models 🚀

Welcome to the World of Machine Learning & Deep Learning!

Are you a developer eager to dive into the exciting realm of Machine Learning (ML) and Deep Learning (DL)? Are you aspiring to master the art of Artificial Intelligence (AI) which is one of the most in-demand skills today? 🎓✨

You've come to the right place! With the rise of AI, the role of an AI Specialist has surged to the top of LinkedIn's "Emerging Jobs" list, with a growth rate of 74% over just a few years! 📈🚀

What You'll Learn:

In this comprehensive course, you will navigate through numerous practical examples that cover a wide array of applications such as image recognition, sentiment analysis, and fraud detection. You'll learn to use cutting-edge frameworks like TensorFlow 2/Keras, NumPy, Pandas, and Matplotlib, and harness the power of platforms like Google Colab for your projects. 🛠️💫

Each example is designed to be independent, allowing you to learn in the order that suits you best. Here's what you'll cover in each hands-on project:

• ✅ Understanding the Problem
• ✅ Data Analysis & Visualization
• ✅ Model Selection
• ✅ Data Preparation for Training & Testing
• ✅ Building, Testing, & Improving a Model
• ✅ Addressing Common Questions
• ✅ Next Steps in Your Machine Learning Journey

Your Instructor: Madhu Siddalingaiah 🧑‍🏫🚀

With a wealth of practical experience and over 20 years of teaching expertise, Madhu is your ideal guide through the complexities of ML. His commitment to quality and ongoing support means you're in capable hands. Plus, he's always ready to answer your questions! ✉️👍

What Students Are Saying:

🌟 "clear explanations...to the point and no jargon..." - Ashraf UI

🌟 "The course is easy to understand and well presented, same thing for the practical examples." - Iheb GANDOUZ

🌟 "The way it is explained is really cool. I used to be bored after an hour during lectures, but the guide somehow makes it very interesting..." - Anu Priya J

Course Updates:

January 2020:

• New mathematics and ML foundation section added.
• All examples updated to TensorFlow 2.
• Introduction to using Jupyter notebooks.
• Python quick start guide included.
• Basic linear algebra concepts covered.

March 2020:

• A new sentiment analysis and natural language processing section with a focus on BERT.

April/May 2020:

• Improvements to assignments for a self-paced or guided approach.
• Additional lectures covering Google Colab, Python quick start, and image classification.

Join us on this journey to master Machine Learning & Deep Learning! 🤗🌟

Enroll now and transform your coding skills into powerful ML applications. Whether you're a beginner or looking to sharpen your expertise, this course will provide you with the knowledge and hands-on experience needed to succeed in the field of AI. 🚀📚

Take the Next Step:

👉 Sign up today and embark on your Machine Learning adventure with confidence! 🎯🎉

Don't just learn, do it by Example! ✨🔍