Neural Networks

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Predictive Analytics using Machine Learning (edX)

Learn how to build predictive models using machine learning. This course will give you an overview of machine learning-based approaches for predictive modelling, including tree-based techniques, support vector machines, and neural networks using Python.
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Visual Perception (Coursera)

Oct 25th 2021
Visual Perception (Coursera)
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The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The [...]
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Neural Networks and Random Forests (Coursera)

Oct 25th 2021
Neural Networks and Random Forests (Coursera)
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In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We’ll start with a deep dive into neural networks, building our knowledge from the ground up by examining the structure and properties. Then we’ll code some simple neural network models and learn [...]
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Machine Learning Models in Science (Coursera)

Oct 25th 2021
Machine Learning Models in Science (Coursera)
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This course is aimed at anyone interested in applying machine learning techniques to scientific problems. In this course, we'll learn about the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms. We'll start with data preprocessing techniques, such as [...]
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Oct 25th 2021
Course Auditing
32.00 EUR/month

Custom Models, Layers, and Loss Functions with TensorFlow (Coursera)

Oct 25th 2021
Custom Models, Layers, and Loss Functions with TensorFlow (Coursera)
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In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network; • Build custom loss functions (including the contrastive loss function used in a Siamese network) in [...]
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Reinforcement Learning for Trading Strategies (Coursera)

In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied [...]
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Visual Perception for Self-Driving Cars (Coursera)

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of [...]
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Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls (Coursera)

Machine learning. Your team needs it, your boss demands it, and your career loves it. After all, LinkedIn places it as one of the top few "Skills Companies Need Most" and as the very top emerging job in the U.S. This course will show you how machine learning works. [...]
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Natural Language Processing with Sequence Models (Coursera)

In Course 3 of the Natural Language Processing Specialization, offered by deeplearning.ai, you will: a) Train a neural network with GLoVe word embeddings to perform sentiment analysis of tweets, b) Generate synthetic Shakespeare text using a Gated Recurrent Unit (GRU) language model, c) Train a recurrent neural network to [...]
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Natural Language Processing with Probabilistic Models (Coursera)

In Course 2 of the Natural Language Processing Specialization, offered by deeplearning.ai, you will: a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming; b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is important for computational linguistics, c) Write a better auto-complete algorithm using [...]
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