Search Results for "deep"
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Showing 1345 open source projects for "deep"
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Deep-Live-Cam
Real time face swap and one-click video deepfake
Real time face swap and one-click video deepfake with only a single image. Choose a face (image with the desired face) and the target image/video (image/video in which you want to replace the face) and click on Start. Open File Explorer and navigate to the directory you select your output to be in. You will find a directory named <video_title> where you can see the frames being swapped in real time. Once the processing is done, it will create the output file. -
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Deep Chat
Customizable AI chat component for websites with API support
Deep Chat is a highly customizable web component designed to simplify the integration of AI-powered chat interfaces into websites. It allows developers to embed a fully functional chatbot using minimal setup, while still offering extensive control over behavior, appearance, and integrations. Deep Chat supports connections to a wide range of AI services as well as custom backends, enabling flexible deployment for different use cases. -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
Deep Research is a local-first research agent that orchestrates multiple LLMs to generate in-depth reports in minutes. It combines “thinking” and “task” model roles with live internet access to plan, search, read, and synthesize findings into structured outputs. The project emphasizes privacy: processing and storage happen locally, avoiding server-side retention of your queries and notes. -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can... -
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Deep Lake
Data Lake for Deep Learning. Build, manage, and query datasets
Deep Lake (formerly known as Activeloop Hub) is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos. -
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Open Deep Research
An AI-powered research assistant that performs iterative research
Deep Research is a lightweight AI research agent designed to autonomously investigate complex topics through iterative web exploration and reasoning. The project combines search engines, web scraping, and large language models to progressively refine its understanding of a user’s query and dive deeper over multiple cycles. Its core goal is to provide the simplest possible implementation of a deep research workflow so developers can study and extend agent behavior without dealing with large, opaque codebases. ... -
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Auto-Deep-Research
Your Fully-Automated Personal AI Assistant
Auto-Deep-Research is a system designed to fully automate deep research workflows using language models, retrieval, planning, and multi-stage reasoning to produce structured research artifacts such as surveys, benchmarks, reports, and even prototypes without heavy human intervention. Users provide a research topic or multifaceted goal, and the system autonomously breaks the objective down into subtasks like literature collection, critical summarization, cross-comparison, citation extraction, metric evaluation, and structured writing. ... -
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Deep Search Agent
Implement a concise and clear Deep Search Agent from 0
Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
Deep-Learning-Is-Nothing presents deep learning concepts in an approachable, from-scratch style that demystifies the stack behind modern models. It typically begins with linear algebra, calculus, and optimization refreshers before moving to perceptrons, multilayer networks, and gradient-based training. Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). -
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Deep Blue Thesaurus Conversion
An open source free input method thesaurus conversion program
An input method thesaurus conversion software, supports the following more than 20 input method tools and thesaurus. This program supports batch conversion (drag and drop multiple thesaurus files at a time, or hold down Ctrl to select multiple files), support command line mode (use -? command to view help under the command line), and support Windows, Linux, and MacOS. Supports Cangjie, Erbi (Super Strong Erbi, Qingsong Erbi, etc.), Pinyin (full spelling, double spelling), Wubi (Wubi 86, Wubi... -
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AI Agent Deep Dive
AI Agent Source Code Deep Research Report
AI Agent Deep Dive is a comprehensive educational repository designed to provide a deep and structured understanding of how modern AI agents work, focusing on architecture, workflows, and real-world implementation patterns. It breaks down complex concepts such as planning, tool usage, memory management, and multi-step reasoning into digestible explanations and practical examples. -
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Deep Research Web UI
AI-powered research assistant that performs iterative, deep research
Deep Research Web UI is an AI-powered research assistant interface designed to automate complex, multi-step information gathering workflows through a combination of search engines, web scraping, and large language models. It operates as a front-end system for deep research agents that iteratively refine queries, retrieve information from multiple sources, and synthesize structured outputs into coherent reports. -
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DEEP
Differential Evolution Entirely Parallel Method
The Differential Evolution, introduced in 1995 by Storn and Price, considers the population, that is divided into branches, one per computational node. The Differential Evolution Entirely Parallel method takes into account the individual age, that is defined as the number of iterations the individual survived without changes. The introduced improvements are: (I) allow several oldest individuals to be overwritten by the same number of best ones in the population, (II) new selection rule uses... -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
Companion notebooks for Deep Learning is a collection of Jupyter notebooks that accompany François Chollet’s deep learning curriculum, providing hands-on implementations of key concepts using practical examples. The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. ... -
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The Machine & Deep Learning Compendium
List of references in my private & single document
The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows. -
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imgclsmob Deep learning networks
Sandbox for training deep learning networks
imgclsmob is a deep learning research repository focused on implementing and experimenting with convolutional neural networks for computer vision tasks. The project serves as a sandbox for training and evaluating a wide variety of neural network architectures used in image analysis. It includes implementations of models used for tasks such as image classification, object detection, semantic segmentation, and pose estimation. -
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Deep Learning Interviews book
Hundreds of fully solved job interview questions
The interviews.ai repository hosts the open materials for the book Deep Learning Interviews, a comprehensive collection of technical questions and fully solved problems covering many aspects of artificial intelligence. The project was created to help students, researchers, and engineers prepare for machine learning and deep learning interviews by providing structured explanations of key concepts. The repository organizes problems across topics such as neural networks, optimization, probabilistic models, and mathematical foundations of machine learning. ... -
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Learn PyTorch for Deep Learning
Materials for the Learn PyTorch for Deep Learning
Learn PyTorch for Deep Learning is an open-source educational repository that provides the full learning materials for the “Learn PyTorch for Deep Learning: Zero to Mastery” course created by Daniel Bourke. The project is designed to teach beginners how to build deep learning models using PyTorch through a hands-on, code-first learning approach. Instead of focusing heavily on theory alone, the repository encourages learners to experiment with code and develop practical machine learning skills through guided examples and exercises. ... -
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Deep Learning Essay Reading
Read classic and new deep learning papers paragraph by paragraph
Deep Learning Essay Reading repository is a comprehensive collection of machine learning and deep learning research summaries designed to make cutting-edge academic work more accessible. Instead of reading entire dense academic papers, contributors provide structured breakdowns and insights into the most influential research from the past decade, often including explanation highlights and key takeaways. -
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Deep-Learning-Interview-Book
Interview guide for machine learning, mathematics, and deep learning
Deep-Learning-Interview-Book collects structured notes, Q&A, and concept summaries tailored to deep-learning interviews, turning scattered study into a coherent playbook. It spans the core math (linear algebra, probability, optimization) and the practitioner topics candidates actually face, like CNNs, RNNs/Transformers, attention, regularization, and training tricks. -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. -
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satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
...You can also follow me on Twitter and LinkedIn where I aim to post frequent updates on my new discoveries, and I have created a dedicated group on LinkedIn. I have also started a blog here and have published a post on the history of this repository called Dissecting the satellite-image-deep-learning repo. -
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PyTorch
Open source machine learning framework
...PyTorch can be used as a replacement for Numpy, or as a deep learning research platform that provides optimum flexibility and speed. -
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InsightFace
State-of-the-art 2D and 3D Face Analysis Project
State-of-the-art deep face analysis library. InsightFace is an open-source 2D&3D deep face analysis library. InsightFace is an integrated Python library for 2D&3D face analysis. InsightFace efficiently implements a wide variety of state-of-the-art algorithms for face recognition, face detection, and face alignment, which are optimized for both training and deployment.
