Search Results for "math with python learn" - Page 3
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Showing 341 open source projects for "math with python learn"
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SKORCH
A scikit-learn compatible neural network library that wraps PyTorch
A scikit-learn compatible neural network library that wraps PyTorch. -
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UMAP
Uniform Manifold Approximation and Projection
Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction. It is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional... -
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Cleanlab
The standard data-centric AI package for data quality and ML
... label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box. -
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CTGAN
Conditional GAN for generating synthetic tabular data
CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may... -
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent... -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking... -
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Baby Buddy
Helps caregivers track sleep, feedings, diaper changes, and tummy time
A buddy for babies! Helps caregivers track sleep, feedings, diaper changes, tummy time and more to learn about and predict baby's needs without (as much) guesswork. A buddy to help caregivers track sleep, feedings, diaper changes, and tummy time to learn about and predict baby's needs without (as much) guess work. A demo of Baby Buddy is available on Heroku. The demo instance resets every hour. Baby Buddy is available in a variety of languages thanks to the efforts of numerous translators... -
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Typer
Typer, build great CLIs, based on Python type hints
Typer is a library for building CLI applications that users will love using and developers will love creating. Based on Python 3.6+ type hints. Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. It's easy to use for the final users. Automatic help, and automatic completion for all shells. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. The simplest example adds only 2 lines... -
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SQLModel
SQL databases in Python, designed for simplicity, compatibility
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. SQLModel is based on Python-type annotations, and powered by Pydantic and SQLAlchemy. -
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NGBoost
Natural Gradient Boosting for Probabilistic Prediction
ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training set... -
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MathTranslate
translate scientific papers in latex, especially arxiv papers
This is a project to translate LaTeX documents, especially scientific papers, from any language to any language. LaTeX expressions like math expressions are perfectly kept unchanged. LaTeX documents can finally be compiled into PDF files. Especially it can be directly applied to translate arXiv papers since it provides the LaTeX source code of most of the papers. -
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TPOT
A Python Automated Machine Learning tool that optimizes ML
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. -
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pmdarima
Statistical library designed to fill the void in Python's time series
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. -
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Godot RL Agents
An Open Source package that allows video game creators
godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot. -
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Lingua-Py
The most accurate natural language detection library for Python
... applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run... -
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peewee
A small, expressive orm, which supports postgresql, mysql and sqlite
Peewee is a simple and small ORM. It has few (but expressive) concepts, making it easy to learn and intuitive to use. Peewee will automatically infer the database table name from the name of the class. You can override the default name by specifying a table_name attribute in the inner “Meta” class (alongside the database attribute). To learn more about how Peewee generates table names, refer to the Table Names section. There are lots of field types suitable for storing various types of data... -
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Dominate
Dominate is a Python library for creating and manipulating HTML docs
Dominate is a Python library for creating and manipulating HTML documents using an elegant DOM API. It allows you to write HTML pages in pure Python very concisely, which eliminates the need to learn another template language, and lets you take advantage of the more powerful features of Python. Dominate can also use keyword arguments to append attributes onto your tags. Most of the attributes are a direct copy from the HTML spec with a few variations. Through the use of the += operator... -
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TensorFlow Model Optimization Toolkit
A toolkit to optimize ML models for deployment for Keras & TensorFlow
... and optimization tool depending on your task. In many cases, pre-optimized models can improve the efficiency of your application. Try the post-training tools to optimize an already-trained TensorFlow model. Use training-time optimization tools and learn about the techniques. -
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talos
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Talos radically changes the ordinary Keras, TensorFlow (tf.keras), and PyTorch workflow by fully automating hyperparameter tuning and model evaluation. Talos exposes Keras and TensorFlow (tf.keras) and PyTorch functionality entirely and there is no new syntax or templates to learn. Talos is made for data scientists and data engineers that want to remain in complete control of their TensorFlow (tf.keras) and PyTorch models, but are tired of mindless parameter hopping and confusing optimization... -
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Ariadne
Python library for implementing GraphQL servers
Ariadne is a Python library for implementing GraphQL servers. Schema-first. Ariadne enables Python developers to use a schema-first approach to the API implementation. This is the leading approach used by the GraphQL community and supported by dozens of frontend and backend developer tools, examples, and learning resources. Ariadne makes all of this immediately available to you and other members of your team. Ariadne offers a small, consistent, and easy to memorize API that lets developers... -
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Ansible Automation Platform Workshops
Training course for Ansible automation platform
The Red Hat Ansible Automation Workshops project is intended for effectively demonstrating Ansible's capabilities through instructor-led workshops or self-paced exercises. These interactive learning scenarios provide you with a pre-configured Ansible Automation Platform environment to experiment, learn, and see how the platform can help you solve real-world problems. The environment runs entirely in your browser, enabling you to learn more about our technology at your pace and time. The demos... -
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OSWorld
Benchmarking Multimodal Agents for Open-Ended Tasks
OSWorld is an open-source synthetic world environment designed for embodied AI research and multi-agent learning. It provides a richly simulated 3D world where multiple agents can interact, perform tasks, and learn complex behaviors. OSWorld emphasizes multi-modal interaction, enabling agents to process visual, auditory, and symbolic data for grounded learning in a simulated world. -
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TextWorld
TextWorld is a sandbox learning environment for the training
TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities.
