Showing 5 open source projects for "probability"

View related business solutions
  • Cut Data Warehouse Costs by 54% Icon
    Cut Data Warehouse Costs by 54%

    Easily migrate from Snowflake, Redshift, or Databricks with free tools.

    BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
    Start Free
  • Veeam Data Platform v13.1 Icon
    Veeam Data Platform v13.1

    Move workloads across hypervisors and clouds with no vendor lock-in. Try VDP free today.

    Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
    Try Now
  • 1
    TensorFlow Probability

    TensorFlow Probability

    Probabilistic reasoning and statistical analysis in TensorFlow

    TensorFlow Probability is a library for probabilistic reasoning and statistical analysis. TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    Pyro

    Pyro

    Deep universal probabilistic programming with Python and PyTorch

    ...It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. Lastly, Pyro gives you the flexibility of automation when you want it, and control when you need it.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 3
    DeepLearning

    DeepLearning

    Deep Learning (Flower Book) mathematical derivation

    ...The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 4
    jieba

    jieba

    Stuttering Chinese word segmentation

    "Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable...
    Downloads: 3 This Week
    Last Update:
    See Project
  • Build Securely on AWS with Proven Frameworks Icon
    Build Securely on AWS with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • 5
    distribution-is-all-you-need

    distribution-is-all-you-need

    The basic distribution probability Tutorial for Deep Learning Research

    ...The material highlights relationships such as conjugate priors and special-case distributions. Examples connect probability functions with machine learning concepts including binary and multiclass cross-entropy. An overview image and presentation summarize the distribution families and their connections for quick reference.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next