Destiny J

Dive into the world of Machine Learning with this hands-on tutoring series designed to equip you with the foundational skills and techniques to build models using Python. Whether you're a beginner or have some coding experience, this series will guide you through key concepts such as supervised and unsupervised learning, data preprocessing, model evaluation, and more. With Python as our tool of choice, you'll learn to implement algorithms like linear regression and neural networks. By the end, you’ll be able to confidently apply Machine Learning techniques to real-world problems and projects. In this series, we'll be covering the following: TensorFlow, Python, linear regression, variables, data analysis, data preprocessing, model evaluation, neural networks. Before the start of the series, I reccomend taking a look at GoogleColab and Tensorflow below are the links: [https://colab.research.google.com/ ](https://www.tensorflow.org/) [https://www.tensorflow.org/](https://www.tensorflow.org/). For your success in this class, I highly recommend having some experience with Python! While we'll cover essential Python libraries and functions for machine learning, having a basic understanding of Python syntax, data structures, and object-oriented programming will help you follow along more smoothly and get the most out of this series. Don't worry if you're new—I'll provide plenty of guidance along the way! Currently, there are only two sessions listed. More will be added soon.