632 Courses delivered Online

A step-by-step guide that walks you through the fundamentals of Python programming followed using Python libraries to create random forest from scratch. A comprehensive course designed for both beginners with some programming experience or even those who know nothing about ML and random forest!

This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.

The course is crafted to help you understand not only the role and impact of recommender systems in real-world applications but also provide hands-on experience in developing complete recommender systems engines for your customized dataset using projects. This learning-by-doing course will help you master the concepts and methodology of Python.

In this course, you will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries and perform exploratory data analysis (EDA) by visualizing a data set using a variety of charts.

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

Learn to design, plan, and scale cloud implementations with Google Cloud Platform's BigQuery. This course will walk you through the fundamentals of applied machine learning and BigQuery ML along with its history, architecture, and use cases.

In this course you will learn how to use the power of Python to train your machine such that your machine starts learning just like human and based on that learning, your machine starts making predictions as well!