#Tutorial-2 = Machine Learning in Python Course Curriculum

Welcome to our comprehensive Machine Learning course in Python! This course is designed for beginners who want to learn the fundamental concepts of Machine Learning and how to implement them using Python.

Machine Learning Play List = https://youtube.com/playlist?list=PL-ecLnTIyON9ZBilJksz6pXcq1MnPfJiZ&feature=shares

In this course, we will start by exploring what Machine Learning is, the various types of Machine Learning, and its applications in the real world. We will also cover the Python environment for Machine Learning and the basics of data preprocessing and feature engineering.

Once we have established the foundations, we will dive into the world of Supervised Learning, where we will cover Linear Regression and Logistic Regression. We will also explore Decision Trees, Random Forests, and Support Vector Machines.

Next, we will discuss Unsupervised Learning and its applications. We will cover Clustering, K-Means, Hierarchical Clustering, and Dimensionality Reduction using Principal Component Analysis (PCA).

Finally, we will cover Deep Learning, including Artificial Neural Networks and Convolutional Neural Networks. We will also explore the popular deep learning frameworks, such as Keras and TensorFlow.

By the end of this course, you will have a solid understanding of Machine Learning concepts and the ability to implement them using Python. Whether you are looking to begin a career in Machine Learning or simply interested in learning more about this exciting field, this course is perfect for you. Join us on this exciting journey into the world of Machine Learning!