Search Results for "deep learning with python" - Page 37
Sort By:
Showing 2106 open source projects for "deep learning with python"
View related business solutions-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools... -
2
Sparrow
Structured data extraction and instruction calling with ML, LLM
Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to... -
3
CineCLI
CineCLI is a cross-platform command-line movie browser
CineCLI is a command-line utility designed to help movie lovers quickly browse, search, and access film information from the terminal without needing a graphical interface. It connects to popular online movie databases to fetch metadata such as titles, release dates, ratings, genres, casts, posters, and plot summaries, presenting all of that in a concise, text-friendly format suitable for terminals or scripts. Users can search by keyword, year, or exact title and then drill into detailed... -
4
Flax
Flax is a neural network library for JAX
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging... -
Paessler - Monitor Your Whole Network in MinutesWaiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
-
5
Courses (Anthropic)
Anthropic's educational courses
Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured... -
6
Tencent-Hunyuan-Large
Open-source large language model family from Tencent Hunyuan
Tencent-Hunyuan-Large is the flagship open-source large language model family from Tencent Hunyuan, offering both pre-trained and instruct (fine-tuned) variants. It is designed with long-context capabilities, quantization support, and high performance on benchmarks across general reasoning, mathematics, language understanding, and Chinese / multilingual tasks. It aims to provide competitive capability with efficient deployment and inference. FP8 quantization support to reduce memory usage... -
7
KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and... -
8
AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal... -
9
Pal
A personal context-agent that learns how you work
Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can... -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
10
Learn Claude Code
Bash is all you need, write a claude code with only 16 line code
Learn Claude Code is an educational repository that teaches how modern AI coding agents work by walking learners through a sequence of progressively more complex agent implementations, starting with a minimal Bash-based agent and culminating in agents with explicit planning, subagents, and skills. It emphasizes a hands-on learning path where each version (from v0 to v4) adds conceptual building blocks like the core agent loop, todo planning, task decomposition, and domain knowledge skills,... -
11
Qwen-Image-Layered
Qwen-Image-Layered: Layered Decomposition for Inherent Editablity
Qwen-Image-Layered is an extension of the Qwen series of multimodal models that introduces layered image understanding, enabling the model to reason about hierarchical visual structures — such as separating foreground, background, objects, and contextual layers within an image. This architecture allows richer semantic interpretation, enabling use cases such as scene decomposition, object-level editing, layered captioning, and more fine-grained multimodal reasoning than with flat image... -
12
NGINX Admin’s Handbook
How to improve NGINX performance, security, and other important things
nginx-admins-handbook is a practical, in-depth guide for configuring, securing, and operating NGINX across real-world deployments. It distills years of research, notes, and field experience into a single handbook that complements the official docs with concrete rules, explanations, and curated external references. The handbook spans fundamentals and advanced topics alike, from HTTP and SSL/TLS basics to reverse proxy patterns, performance tuning, debugging workflows, and hardening... -
13
GLM-4.5
GLM-4.5: Open-source LLM for intelligent agents by Z.ai
GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for... -
14
E2B Cookbook
Examples of using E2B
E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code... -
15
Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. -
16
Step-Audio-EditX
LLM-based Reinforcement Learning audio edit model
Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level... -
17
Agent Apprenticeship
The living ecosystem where AI agents complete tasks
Agent Apprenticeship is an open infrastructure project for turning real AI-agent work into reusable learning signals. It lets local agents complete tasks through iterative workflow loops, then records the process as experience that can improve future agents. Apprentice agents can be paired with mentor agents, human reviewers, or domain experts depending on the selected mode. The project supports Codex, Cursor, Claude Code, OpenClaw, OpenCode, Hermes Agent, and custom agent commands. Its seed... -
18
Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It... -
19
Cheat on Content
Workflow that turns every post into a calibrated experiment
Cheat on Content is an AI-assisted workflow for creators who want to make content performance measurable instead of relying on instinct alone. It turns every post into a structured experiment by asking creators to score ideas, make blind predictions, publish, review results after a defined time window, and evolve their own content rubric. Rather than generating posts for the creator, it focuses on sharpening judgment and helping users understand why certain content performs better. The... -
20
GPTImage2Skill
GPT Image 2 prompt gallery, image prompt library, agentic skill
GPTImage2Skill is a curated prompt gallery, agent skill, and command-line workflow for working with GPT Image 2 generation and editing. It provides reusable image prompts across creative, technical, academic, interface, design, photography, typography, gaming, anime, map, tattoo, and reference-editing use cases. The project is designed to help agents and users produce stronger visual outputs without starting from a blank prompt every time. Its gallery is organized into category files so an... -
21
OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also... -
22
Instill Core
Instill Core is a full-stack AI infrastructure tool for data
Instill Core is an open-source, full-stack AI infrastructure platform designed to orchestrate data pipelines, machine learning models, and unstructured data processing into a unified, production-ready system. It provides an end-to-end solution that enables developers to build, deploy, and manage AI-powered applications without needing to manually stitch together multiple tools across the data and model lifecycle. The platform focuses heavily on handling unstructured data such as documents,... -
23
EvoAgentX
Self-evolving AI agent framework for automated workflows
EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows,... -
24
Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such... -
25
MetaScreener
AI-powered tool for efficient abstract and PDF screening
MetaScreener is an open-source AI-assisted tool designed to streamline the screening process in systematic literature reviews and academic research workflows. The system helps researchers analyze large collections of academic abstracts and research papers to determine which studies are relevant for inclusion in evidence synthesis projects. Instead of manually reviewing hundreds or thousands of documents, researchers can use MetaScreener to apply machine learning techniques that assist with...
