Machine Learning, Data Science and Deep Learning with Python

Build artificial neural networks with Tensorflow and Keras Classify images, data, and sentiments using deep learning Make predictions using linear regression, polynomial regression, and multivariate regression Data Visualization with MatPlotLib and Seaborn Implement machine learning at massive scale with Apache Spark's MLLib Understand reinforcement learning - and how to build a Pac-Man bot Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA Use train/test and K-Fold cross validation to choose and tune your models Build a movie recommender system using item-based and user-based collaborative filtering Clean your input data to remove outliers Design and evaluate A/B tests using T-Tests and P-Values You'll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software. Some prior coding or scripting experience is required. At least high school level math skills will be required. You'll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer.