Category: Intermediate Track

This course will teach you how deep learning builds on machine learning. Then you’ll get a chance to learn more about deep neural networks and advanced architectures such as convolutional networks and recurrent networks. You’ll get hands-on experience building your own state-of-the-art …

Mlcourse.ai an open Machine Learning course by OpenDataScience designed to balance theory and practice. It also offers several Kaggle Inclass competitions for self-assessment. Learn here: MLcourse.ai …

This Machine Learning 501 course by Intel structured around 12 weeks of lectures and exercises covers concepts such as supervised learning algorithms, underfitting, overfitting, regularization, cross validation, parameter tuning and model validation. Learn here: Machine Learning 501 …

This is a collection of free courses from Microsoft that covers pre-trained AI services like Cognitive Services and Bot Framework, as well as deep learning tools like Azure Machine Learning, Visual Studio Code Tools for AI, and Cognitive Toolkit. Learn here: Microsoft …

Are you interested in how AI is applied in robotics? Are you curious on building a self driving car? This free course covers basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus …

In this video recorded from Deep Indaba 2017, Nyalleng and Willie Brink cover ML and why it exists, the learning process as an optimization process, data cleanup , feature selection and improving model performance. Learn here: Fundamentals of Machine Learning …

This online machine learning course is perfect for those who have a solid basis in R and statistics, but are complete beginners with machine learning. After a broad overview of the discipline’s most common techniques and applications, you’ll gain more insight into …

This is a collection of videos covering Statistical machine learning classes from Carnegie Melon University. The topics covered include: Linear regression, Nonparametric regression, Trend Filtering, Linear Classification, Nonparametric classification, Minimax Theory, Nonparametric Bayes, Clustering, Boosting, Graphical Models,, and Dimension Reduction. Learn here …

This crash course from Google covers many machine learning fundamentals, starting with loss and gradient descent, then building through classification models and neural nets. The programming exercises introduce TensorFlow. You’ll watch brief videos from Google machine learning experts, read short text lessons, …