Machine Learning Tutorial

Navigate the perils of model drift and explore our practical guide to data drift monitoring.

Learn about data augmentation techniques, applications, and tools with a TensorFlow and Keras tutorial.

Learn about the most popular model-free reinforcement learning algorithm with a Python tutorial.

Take a deep dive into what MLflow is and how you can leverage this open-source platform for tracking and deploying your machine learning experiments.

Discover everything you need to know about Kubeflow and explore how to build and deploy Machine Learning Pipelines

Learn what the normal equation is and how can you use it to build machine learning models.

Learn about the lasso and ridge techniques of regression. Compare and analyse the methods in detail.

Learn how gradient descent optimizes models for machine learning. Discover its applications in linear regression, logistic regression, neural networks, and the key types including batch, stochastic, and mini-batch gradient descent.

Learn about the most popular deep learning model RNN and get hands-on experience by building a MasterCard stock price predictor.

Learn basic MLOps and end-to-end development and deployment of ML pipelines.

Learn about how learning curves can help you evaluate your data and identify optimal solutions.

Prepare for your first Kaggle Competition with this step-by-step tutorial.