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Here’s everything you need to know 👇 I developed a machine learning model with @Eight Sleep and we just released it today 1️⃣ What data was it built on? This model was built on the largest raw biosignal dataset ever used to train an AI, from any device, including every wearable on the market. 2.04 million hours 136,575 participants 498k sessions 122 million segments 2️⃣ What can it predict? It can predict your biological age (the age your body acts like) within 3.3 years. It also predicts heart
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Instead of importing PyTorch, this project makes you build your own version of it. TrenTorch is the coding curriculum that forces you to build your own machine learning framework instead of just importing one. Most people treat neural networks like a black box, but this project makes you write every single line of code on plain NumPy to recreate the actual machinery of PyTorch. It breaks the work into twenty progressive steps, guiding you from basic math all the way to building a real language m
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The Multi-Layer Perceptron (MLP) is a foundational class of feedforward artificial neural networks. It consists of at least three layers of nodes: an input layer, one or more hidden layers, and an output layer. Except for the input nodes, each node is a neuron that uses a nonlinear activation function, such as ReLU or Sigmoid. This nonlinearity allows MLPs to solve complex, non-linearly separable problems, distinguishing them from simpler linear perceptrons.The true power of an MLP lies in its t
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The study behind this is unusually practical. Dunigan Folk, Mirka Henninger and Elizabeth Dunn at the University of British Columbia took two waves of the American Time Use Survey, more than 15,000 people accounting for how they spent a single day, and used machine learning to find what separated a better-than-typical day from an ordinary one. The thresholds are the useful part. Socializing helped, and then flattened out after about two hours. Work didn't hurt a day until it passed six. Passive
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10 GitHub repos to build your quant toolkit: indicators, market data, backtesting, machine learning, and derivatives. #quantfinance #github #python #algotrading
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