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  • 1
    Stock prediction deep neural learning

    Stock prediction deep neural learning

    Predicting stock prices using a TensorFlow LSTM

    Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock...
    Downloads: 7 This Week
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  • 2
    Penzai

    Penzai

    A JAX research toolkit to build, edit, & visualize neural networks

    Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. ...
    Downloads: 0 This Week
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  • 3
    Haiku

    Haiku

    JAX-based neural network library

    ...Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. ...
    Downloads: 0 This Week
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  • 4
    TensorNetwork

    TensorNetwork

    A library for easy and efficient manipulation of tensor networks

    ...Because it supports backends such as NumPy, TensorFlow, PyTorch, and JAX, the same model can run on CPUs, GPUs, or TPUs with minimal code changes. Tutorials and visualization helpers make it easier to understand how network topology affects expressive power and computational cost.
    Downloads: 0 This Week
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  • 5
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. ...
    Downloads: 0 This Week
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  • 6
    PyTorch Natural Language Processing

    PyTorch Natural Language Processing

    Basic Utilities for PyTorch Natural Language Processing (NLP)

    ...Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings.
    Downloads: 2 This Week
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