About the courseMachine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.
About the courseThis Machine Learning with R course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
About the courseGet hands-on experience creating and training machine learning models so that you can predict what animal is making a specific sound, like a cat purring or a dog barking. Integrate those models in a simple web page that you build in Node-RED. Then, add visual recognition so that you can identify the image of an animal.
About the courseWelcome to this machine learning course on Dimensionality Reduction. Dimensionality Reduction is a category of unsupervised machine learning techniques used to reduce the number of features in a dataset. Dimension reduction can also be used to group similar variables together. In this course, you will learn the theory behind dimension reduction, and get some hands-on practice using Principal Components Analysis (PCA) and Exploratory Factor Analysis (EFA) on survey data. The code used in this course is prepared for you in R.
About the courseApache SystemML is a declarative style language designed for large-scale machine learning. It provides automatic generation of optimized runtime plans ranging from single-node, to in-memory, to distributed computations on Apache Hadoop and Apache Spark. SystemML algorithms are expressed in R-like or Python-like syntax that includes linear algebra primitives, statistical functions and ML-specific constructs.
About the courseMajority of data in the world are unlabeled and unstructured data, for instance images, sound, and text data. Shallow neural networks cannot easily capture relevant structure in these kind of data, but deep networks are capable of discovering hidden structures within these data. In this course, you will use TensorFlow library to apply deep learning on different data types to solve real world problems.
How to obtain your certificate for the "Machine Learning Essentials" learning path
- Step 1: Enrol in every course above.
- Step 2: Successfully pass and receive a certificate for each of the courses.
- Step 3: Return here and click the button below to view your certificate: