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The Joy of Designing Deep Neural Networks
Bradley Arsenault shares the joy he felt the first time he designed a deep neural network, and how simple intuitions on neural networks have led to greater designs and accuracy.
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Comparing Machine Learning Strategies Using Scikit-Learn and TensorFlow
Oliver Zeigermann looks at different ML strategies -KNN, Decision Trees, Support Vector Machines, and Neural Networks- and visualizes how they make predictions by plotting their decision boundaries.
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Applying Deep Learning to Airbnb Search
Malay Haldar discusses the work done in applying neural networks at Airbnb to improve the search beyond the results obtained with ML.
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Understanding Deep Learning
Jessica Yung talks about the foundational concepts about neural networks and highlights key things to pay attention to: learning rates, how to initialize a network, and more.
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AI for Software Testing with Deep Learning: Is It Possible?
Emerson Bertolo discusses lessons learned when using pre-trained Convolutional Neural Networks (CNN) models, Image Detection APIs and CNN's built from scratch for this purpose.
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Rethinking HCI with Neural Interfaces @CTRLlabsCo
Adam Berenzweig talks about brain-computer interfaces, neuromuscular interfaces, and other biosensing techniques that can eliminate the need for physical controllers.
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Teaching a Machine to Code
Samir Talwar discusses different techniques, architectures and optimizations tried in the process of teaching a machine to write code using neural networks, simulations and everything in between.
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Neural Networks across Space and Time
Dave Snowdon starts with a brief introduction to deep neural networks, why they are important and how they work. He covers 2 of the most important deep neural architectures: convolutional & recurrent.
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Interpretable Machine Learning Products
Mike Lee Williams discusses how interpretability can make deep neural networks models easier to understand, and describes LIME, an OS tool that can be used to explore what ML classifiers are doing.
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Self-Racing Using Deep Neural Networks: Lap 2
Jendrik Joerdening and Anthony Navarro discuss how a team of Udacity students used neural networks to teach a car to drive by itself around a track in two days.
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Primer on Neural Networks
Chase Aucoin introduces neural networks with examples and simple breakdowns about the math involved in a way accessible to a large audience.
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