Search Results for "deep learning with python" - Page 41
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Showing 2106 open source projects for "deep learning with python"
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NVIDIA Merlin
Library providing end-to-end GPU-accelerated recommender systems
...Transform data (ETL) for preprocessing and engineering features. Accelerate your existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built data loaders. Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code. -
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Zero to Mastery Deep Learning TensorFlow
All course materials for the Zero to Mastery Deep Learning with TF
This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. -
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Computer Vision in Action
A computer vision closed-loop learning platform
Computer Vision in Action is a practical, example-rich repository that demonstrates real-world applications of computer vision techniques and algorithms in Python, often using OpenCV, deep learning models, and related tooling. It serves as a hands-on companion for learners and engineers who want to understand not just the theory, but how computer vision is actually implemented for tasks like object detection, image classification, feature tracking, optical flow, and image segmentation. The repository includes structured code examples, scripts, and notebooks that cover pipeline construction, preprocessing, model inference, and visual output rendering, making it easy for newcomers or intermediate practitioners to adapt patterns to their own projects. ... -
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UAVs Predictive Maintenance
Vibration-Based Structural Health Monitoring of UAVs
This study presents an integrated software application that enables vibration-based structural health monitoring within a closed-loop Product Lifecycle Management (PLM) framework. The system collects time-domain vibration data from UAV components during the pre-flight phase and applies deep learning architectures—including Gated Recurrent Units (GRUs), Long Short-Term Memory networks (LSTMs), and Convolutional Neural Networks (CNNs)—for accurate fault classification. Communication with the UAV is handled through the DroneKit-Python API, while RESTful APIs interface with the Aras Innovator PLM platform to automate data exchange and support predictive maintenance. ... -
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MicroTile-Offline-Map-Downloader
A compact Python tool that saves tiny, single-zoom offline maps.
An optimized Python map assistant designed to download highly compact, single-zoom offline database packages for zero-connectivity situations. The application dynamically balances storage by locking local use to a macro grid layout while automatically unlocking unrestricted, high-resolution deep zooming whenever an internet connection is available. -
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Universal Sentence Encoder
Encoder of greater-than-word length text trained on a variety of data
The Universal Sentence Encoder (USE) is a pre-trained deep learning model designed to encode sentences into fixed-length embeddings for use in various natural language processing (NLP) tasks. It leverages Transformer and Deep Averaging Network (DAN) architectures to generate embeddings that capture the semantic meaning of sentences. The model is designed for tasks like sentiment analysis, semantic textual similarity, and clustering, and provides high-quality sentence representations in a computationally efficient manner. -
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sadsa
SADSA (Software Application for Data Science and Analytics)
SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code. -
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ResoRefine-AI
Free AI Audio Enhancer & Noise Reduction tool for Windows.
... •100% Private & Offline: Your audio never goes to the cloud. It processes entirely locally via AI engine. •Remove Noise & Echo: Instantly clean up mic hiss, fan noise, and room echo using deep-learning suppression. •Studio Desk Control: Dial in "Broadcast Warmth" (Bass) and "Vocal Clarity" (Treble) for a rich, professional podcast sound. •Auto-Leveling: Built-in studio compression ensures perfectly balanced, clear audio for YouTube, Instagram, and TikTok. -
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Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state-of-the-art (surpassing SimCLR) without contrastive learning and having to designate negative pairs. This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique... -
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Datapipe
Real-time, incremental ETL library for ML with record-level depend
Datapipe is a real-time, incremental ETL library for Python with record-level dependency tracking. Datapipe is designed to streamline the creation of data processing pipelines. It excels in scenarios where data is continuously changing, requiring pipelines to adapt and process only the modified data efficiently. This library tracks dependencies for each record in the pipeline, ensuring minimal and efficient data processing. -
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DeepChem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, etc
DeepChem aims to provide a high-quality open-source toolchain that democratizes the use of deep learning in drug discovery, materials science, quantum chemistry, and biology. DeepChem currently supports Python 3.7 through 3.9 and requires these packages on any condition. DeepChem has a number of "soft" requirements. If you face some errors like ImportError: This class requires XXXX, you may need to install some packages. Deepchem provides support for TensorFlow, PyTorch, JAX and each requires an individual pip Installation. ... -
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tslab
Interactive JavaScript and TypeScript programming with Jupyter
tslab is an interactive programming environment and REPL with Jupyter for JavaScript and TypeScript users. You can write and execute JavaScript and TypeScript interactively on browsers and save results as Jupyter notebooks. -
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eduActiv8
A collection of interactive educational exercises
eduActiv8 is a free Open Source multi-platform educational application that aims to assist in learning various early education topics - from learning the alphabet and new words, colours, time to a wide range of maths-related subjects. eduActiv8 is a continuation of the development of the pySioGame project just under a new name. It is being developed on GitHub at: https://github.com/imiolek-ireneusz/eduActiv8 but 'compiled' releases are published here. The latest version has been... -
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OpenFace Face Recognition
Face recognition with deep neural networks
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. -
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CodeCampus
CodeCampus is a learning-first Linux OS for CSE and IT students
CodeCampus OS is a custom Linux distribution based on Ubuntu 24, designed for beginner developers, computer science students, and self-learners who want to start coding without friction. Unlike traditional setups that require hours of installation and configuration, CodeCampus provides a fully pre-configured, learning-first environment right out of the box. From the moment you boot, everything is ready—so you can focus on learning, experimenting, and building instead of... -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
...He has tact only (blind agent). The video shows learning, planning, executing and plan optimization. -
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ActiveVPN
The Ultimate Network Privacy & VPN Detection Tool
ActiveVPN inspects your system's network interfaces, analyzes running processes, checks your external IP against known hosting providers, and performs DNS leak tests — all in one hacker-style terminal UI. It tells you whether your VPN is actually working. -
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NZMATH
Python Calculator on Number Theory, three-birds-one learning material
NZMATH is a Python calculator on number theory. It is freely available and distributed under the BSD license. All programs are written only by Python so that you can easily see their algorithmic number theory. You can get NZMATH with a single command: % python -m pip install -U nzmath Here % is the command line prompt of Windows or Unix/macOS. -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research... -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. OWL (Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation) is an advanced framework designed to enhance multi-agent collaboration, improving task automation across various domains. By utilizing dynamic agent interactions, OWL aims to streamline and optimize complex workflows, making AI collaboration more natural, efficient, and adaptable. It is built on... -
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FileSentinel
Simple Python file integrity checker for defensive security
FileSentinel is an open-source Python tool that helps users monitor folders for unexpected file changes. It creates a baseline using SHA-256 hashes and later compares the folder against that baseline to detect added, modified, and deleted files. It is designed as a beginner-friendly defensive security utility for students, small offices, and anyone learning basic file integrity monitoring. -
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SMILI
Scientific Visualisation Made Easy
The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with... -
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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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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. ... -
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MobileNetV2
SSD-based object detection model trained on Open Images V4
MobileNetV2 is a highly efficient and lightweight deep learning model designed for mobile and embedded devices. It is based on an inverted residual structure that allows for faster computation and fewer parameters, making it ideal for real-time applications on resource-constrained devices. MobileNetV2 is commonly used for image classification, object detection, and other computer vision tasks, achieving high accuracy while maintaining a small memory footprint.
