Effective data communication is more important now than ever! Understanding the presentation side of data is a growing skill gap across all industries. By becoming an efficient data translator, you position yourself as a critical part of any team.

This course covers conceptual and practical aspects of pre-processing images to maximize the efficacy of image processing algorithms, as well as implementing feature extraction, dimensionality reduction, and latent factor identification.

This course covers various techniques for encoding categorical data, starting with the familiar forms of one-hot and label encoding, before moving to contrast coding schemes such as simple coding, Helmert coding, and orthogonal polynomial coding.

This course exhaustively covers data preprocessing techniques and transforms available in scikit-learn, allowing the construction of highly optimized features that are scaled, normalized and transformed in mathematically sound ways to fully harness the power of machine learning techniques.

This course covers aspects of extracting information from text documents and constructing classification models including feature vectorization, locality-sensitive hashing, stopword removal, lemmatization, and more from natural language processing.

Start creating mesmerizing graphics & charts with R programming from scratch!!

In this course, you'll learn how to make use of SSRS features to create interactive reports. The reports will become dynamic for users by using functionalities such as drilldown, drill through, interactive sorting, jump actions, and document maps.

This course course will help engineers and data scientists learn how to build machine learning models using scikit-learn, one of the most popular ML libraries in Python. No prior experience with ML needed, only basic Python programming knowledge.

Training ML models is a compute-intensive operation and is best done in a distributed environment. This course will teach you how Spark can efficiently perform data explorations, cleaning, aggregations, and train ML models all on one platform.

BigQuery ML on the Google Cloud Platform democratizes machine learning by allowing data analysts and engineers to build and use machine learning models directly from SQL without using any higher level programming language.

This course leads you through the necessary steps to create a multidimensional model, explains essential concepts unique to online analytical processing, and shows you how to manage data storage and model updates on an ongoing basis.

This course covers all the important aspects of support currently available in scikit-learn for the construction and training of neural networks, including the perceptron, MLPClassifier, and MLPRegressor, as well as Restricted Boltzmann Machines.