Search Results for "artificial intelligence programming assistent"
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Showing 38 open source projects for "artificial intelligence programming assistent"
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Professional Streaming and Video Hosting - GDPR Compliant - 3Q3Q offers a multifunctional video platform for hosting, managing and distributing video and audio content on all channels. Live and on-demand.
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Polygon Software | Apparel Software | PLM and ERP SolutionsPolyPM is an integrated enterprise resource planning (ERP) and product lifecycle management (PLM) solution developed by Polygon Software. Built for small to medium-sized apparel manufacturers, PolyPM enables businesses to integrate all aspects of the product development, supply chain and production processes, as well as instantly access all their style and manufacturing information anywhere in the world. This allows businesses to shorten time-to-market, incur lower development costs, and improve customer service and worker productivity.
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in... -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,... -
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fklearn
Functional Machine Learning
fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning. -
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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... -
CloudZero: The Cloud Cost Optimization PlatformCloudZero is the leader in proactive cloud cost efficiency. We enable engineers to build cost-efficient software without slowing down innovation. CloudZero's next-generation cloud cost optimization platform automates the collection, allocation, and analysis of cloud costs to uncover savings opportunities and improve unit economics. We are the only platform that enables companies to understand 100% of their operational cloud spend and take an engineering-led approach to optimizing that spend. CloudZero is used by industry leaders worldwide, such as Coinbase, Klaviyo, Miro, Nubank, and Rapid7.
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. By solving progressively... -
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Flower
Flower: A Friendly Federated Learning Framework
A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new... -
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Amazing-Python-Scripts
Curated collection of Amazing Python scripts
Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning... -
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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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TorchCode
Practice implementing softmax, attention, GPT-2 and more
TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,... -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. Each example is designed to illustrate a single concept or application in a clear and concise manner so that learners can quickly understand the underlying logic. ... -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can... -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and... -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. 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... -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,... -
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TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including... -
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Haiku Sonnet for JAX
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. 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 provides two core tools: a module abstraction, hk.Module, and a... -
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Diffrax
Numerical differential equation solvers in JAX
Diffrax is a numerical differential equation solving library built for the JAX ecosystem, with a strong focus on composability, differentiability, and high-performance scientific computing. The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with... -
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Data Science Interviews
Data science interview questions and answers
Data Science Interviews is an open-source repository that collects common data science interview questions along with community-provided answers and explanations. The project serves as a preparation resource for students, job seekers, and professionals who want to review the technical knowledge required for data science roles. The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or... -
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PyCaret
An open-source, low-code machine learning library in Python
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. This makes experiments exponentially fast and... -
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zvt
Modular quant framework
For practical trading, a complex algorithm is fragile, a complex algorithm building on a complex facility is more fragile, complex algorithm building on a complex facility by a complex team is more and more fragile. zvt wants to provide a simple facility for building a straightforward algorithm. Technologies come and technologies go, but market insight is forever. Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt.... -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,... -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already... -
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CodeContests
Large dataset of coding contests designed for AI and ML model training
CodeContests, developed by Google DeepMind, is a large-scale competitive programming dataset designed for training and evaluating machine learning models on code generation and problem solving. This dataset played a central role in the development of AlphaCode, DeepMind’s model for solving programming problems at a human-competitive level, as published in Science. CodeContests aggregates problems and human-written solutions from multiple programming competition platforms, including AtCoder,... -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. Its architecture automatically divides large...
