Search Results for "math with python learn" - Page 8

Showing 493 open source projects for "math with python learn"

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  • 1
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    ... features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc.
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  • 2
    BCI

    BCI

    BCI: Breast Cancer Immunohistochemical Image Generation

    Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix. We have released the trained model on BCI and LLVIP datasets. We host a competition for breast cancer immunohistochemistry image generation on Grand Challenge. Project pix2pix provides a python script to generate pix2pix training data in the form of pairs of images {A,B}, where A and B are two different depictions of the same underlying scene, these can be pairs {HE, IHC}. Then we can learn to translate A(HE images...
    Downloads: 0 This Week
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  • 3
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no...
    Downloads: 1 This Week
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  • 4
    Emb-GAM

    Emb-GAM

    An interpretable and efficient predictor using pre-trained models

    ... for each input before learning a linear model in the embedding space. The final model (which we call Emb-GAM) is a transparent, linear function of its input features and feature interactions. Leveraging the language model allows Emb-GAM to learn far fewer linear coefficients, model larger interactions, and generalize well to novel inputs. Across a variety of natural-language-processing datasets, Emb-GAM achieves strong prediction performance without sacrificing interpretability.
    Downloads: 0 This Week
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  • 5

    3D Learn to Read Music Game in Python

    3D Learn to Read Music Game in Python

    The game runs on win 7 after its run in win XP compatiability mode (so right click on game to select the SP3). This game to help beginners learn to read sheet music in a fun and easy way. More specifically this game is to learn sheet music restricted to the treble staff and (optionally) their ear training for the treble staff. This Panda3D game project is composed of 7 sub-programs in the project-one program is to deal with the menu, another is the main game code, another program deals...
    Downloads: 1 This Week
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  • 6
    Yellowbrick

    Yellowbrick

    Visual analysis and diagnostic tools to facilitate ML selection

    Yellowbrick extends the Scikit-Learn API to make model selection and hyperparameter tuning easier. Under the hood, it’s using Matplotlib. Yellowbrick is a suite of visual diagnostic tools called "Visualizers" that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, Yellowbrick combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow.
    Downloads: 0 This Week
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  • 7
    Hello AI World

    Hello AI World

    Guide to deploying deep-learning inference networks

    Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train...
    Downloads: 1 This Week
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  • 8
    SageMaker Scikit-Learn Extension

    SageMaker Scikit-Learn Extension

    A library of additional estimators and SageMaker tools based on scikit

    A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install...
    Downloads: 0 This Week
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  • 9
    Reskin Sensor Library

    Reskin Sensor Library

    ReSkin Sensor Interfacing Library

    ... learning and magnetic sensing to offer a low-cost, diverse and compact solution for long-term use. Magnetic sensing separates the electronic circuitry from the passive-interface, making it easier to replace interfaces as they wear out while allowing for a wide variety of form factors. Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement.
    Downloads: 0 This Week
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  • 10
    DALL·E Mini

    DALL·E Mini

    Generate images from a text prompt

    DALL·E Mini, generate images from a text prompt. OpenAI had the first impressive model for generating images with DALL·E. Craiyon/DALL·E mini is an attempt at reproducing those results with an open-source model. The model is trained by looking at millions of images from the internet with their associated captions. Over time, it learns how to draw an image from a text prompt. Some concepts are learned from memory as they may have seen similar images. However, it can also learn how to create...
    Downloads: 13 This Week
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  • 11
    nlpaug

    nlpaug

    Data augmentation for NLP

    This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together.
    Downloads: 0 This Week
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  • 12
    Walrus

    Walrus

    Lightweight Python utilities for working with Redis

    The purpose of walrus is to make working with Redis in Python a little easier. Rather than ask you to learn a new library, walrus subclasses and extends the popular redis-py client, allowing it to be used as a drop-in replacement. In addition to all the features in redis-py, walrus adds support for some newer commands, including full support for streams and consumer groups. Persistent structures implemented on top of Hashes. Supports secondary indexes to allow filtering on equality, inequality...
    Downloads: 0 This Week
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  • 13
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what...
    Downloads: 2 This Week
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  • 14
    gplearn

    gplearn

    Genetic Programming in Python, with a scikit-learn inspired API

    gplearn implements Genetic Programming in Python, with a scikit-learn-inspired and compatible API. While Genetic Programming (GP) can be used to perform a very wide variety of tasks, gplearn is purposefully constrained to solving symbolic regression problems. This is motivated by the scikit-learn ethos, of having powerful estimators that are straightforward to implement. Symbolic regression is a machine learning technique that aims to identify an underlying mathematical expression that best...
    Downloads: 1 This Week
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  • 15
    ModelFox

    ModelFox

    ModelFox makes it easy to train, deploy, and monitor ML models

    ModelFox makes it easy to train, deploy, and monitor machine learning models. Train a model from a CSV file on the command line. Make predictions from Elixir, Go, JavaScript, PHP, Python, Ruby, or Rust. Learn about your models and monitor them in production from your browser. ModelFox makes it easy to train, deploy, and monitor machine learning models. You can install the modelfox CLI by either downloading the binary from the latest GitHub release or by building from source. Train a machine...
    Downloads: 0 This Week
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  • 16
    YOLOv3

    YOLOv3

    Object detection architectures and models pretrained on the COCO data

    Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an expert...
    Downloads: 303 This Week
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  • 17
    Awesome Conformal Prediction

    Awesome Conformal Prediction

    A professionally curated list of awesome Conformal Prediction videos

    awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing...
    Downloads: 0 This Week
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  • 18
    The fastai book

    The fastai book

    The fastai book, published as Jupyter Notebooks

    These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. These notebooks are used for a MOOC and form the basis of this book, which is currently available for purchase. It does not have the same GPL restrictions that are on this repository. The code in the notebooks and python .py files is covered by the GPL v3 license; see the LICENSE file for details. The remainder (including all...
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  • 19
    LayoutParser

    LayoutParser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

    With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser...
    Downloads: 0 This Week
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  • 20
    lightning library

    lightning library

    Large-scale linear classification, regression and ranking in Python

    lightning is a library for large-scale linear classification, regression and ranking in Python.
    Downloads: 0 This Week
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  • 21
    mlcourse.ai

    mlcourse.ai

    Open Machine Learning Course

    mlcourse.ai is an open Machine Learning course by OpenDataScience (ods.ai), led by Yury Kashnitsky (yorko). Having both a Ph.D. degree in applied math and a Kaggle Competitions Master tier, Yury aimed at designing an ML course with a perfect balance between theory and practice. Thus, the course meets you with math formulae in lectures, and a lot of practice in a form of assignments and Kaggle Inclass competitions. Currently, the course is in a self-paced mode. Here we guide you through the self...
    Downloads: 0 This Week
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  • 22
    Raiden Network

    Raiden Network

    Raiden Network

    Use Raiden to enrich your dApp with nearly instant, low-fee and scalable payments. It comes with an easy-to-use API and is compatible with the Ethereum ERC20 token standard. Incentivized, decentralized P2P live streaming with micropayments using Raiden, introducing “Proof-of-Stream-Payment”. The Raiden Network is an infrastructure layer on top of the Ethereum Blockchain. While the basic idea is simple, the underlying protocol is quite complex and the implementation non-trivial. Nonetheless...
    Downloads: 0 This Week
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  • 23
    Feature-engine

    Feature-engine

    Feature engineering package with sklearn like functionality

    Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow Scikit-learn's functionality with fit() and transform() methods to learn the transforming parameters from the data and then transform it.
    Downloads: 0 This Week
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  • 24
    PySchool

    PySchool

    Installable / Portable Python Distribution for Everyone.

    PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4...
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    Downloads: 816 This Week
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  • 25
    Scikit-Optimize

    Scikit-Optimize

    Sequential model-based optimization with a `scipy.optimize` interface

    Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn.
    Downloads: 0 This Week
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