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Our Courses
Introduction to Deep Learning & Neural Networks with Keras
Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks?
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Course by
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Self Paced
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8 hours
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English
Diabetes Disease Detection with XG-Boost and Neural Networks
In this project-based course, we will build, train and test a machine learning model to detect diabetes with XG-boost and Artificial Neural Networks. The objective of this project is to predict whether a patient has diabetes or not based on their given features and diagnostic measurements such as number of pregnancies, insulin levels, Body mass index, age and blood pressure.
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Course by
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Self Paced
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2 hours
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English
Predicting the Weather with Artificial Neural Networks
In this one hour long project-based course, you will tackle a real-world prediction problem using machine learning.
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Course by
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Self Paced
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2 hours
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English
Interpretable machine learning applications: Part 3
In this 50 minutes long project-based course, you will learn how to apply a specific explanation technique and algorithm for predictions (classifications) being made by inherently complex machine learning models such as artificial neural networks.
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Course by
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Self Paced
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3 hours
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English
Build Decision Trees, SVMs, and Artificial Neural Networks
There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and support-vector machines (SVMs) are two examples of algorithms that can both solve regression and classification problems, but which have different applications. Likewise, a more advanced approach to machine learning, called deep learning, uses artificial neural networks (ANNs) to solve these types of problems and more.
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Course by
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Self Paced
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22 hours
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English
An Introduction to Practical Deep Learning
This course provides an introduction to Deep Learning, a field that aims to harness the enormous amounts of data that we are surrounded by with artificial neural networks, allowing for the development of self-driving cars, speech interfaces, genomic sequence analysis and algorithmic trading. You will explore important concepts in Deep Learning, train deep networks using Intel Nervana Neon, apply Deep Learning to various applications and explore new and emerging Deep Learning topics.
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Course by
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Self Paced
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17 hours
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English