Search Results for "deep learning with python" - Page 9
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228 programs for "deep learning with python" with 1 filter applied:
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Deliver secure remote access with OpenVPN.OpenVPN's products provide scalable, secure remote access — giving complete freedom to your employees to work outside the office while securely accessing SaaS, the internet, and company resources.
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EcoAccess is a non-profit organization. Our mission is to empower people to make informed decisions, using the Internet, that address the root causes of environmental challenges. We are building a free community web site where anyone can ask environmental
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Fle3 is a web-based learning environment written in python for Zope. This Sourceforge project is inactive at the moment - click the Homepage link to go where the action's at.
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The Ottawa Python Authors Group is devoted to learning, using, and providing resources to the Python programming language.
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PySometric is an Isometric RPG written in Python. It uses PyGame for graphics, and will feature online play through a peer to peer network. Most of the programmers are learning how to program a 2-d game, and all new programmers are welcome.
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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pySPACE
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due... -
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PySet is an incremental implementation of the classic logic/card game Set, built using Python, Simple Direct-media Library (SDL), and PyGame (a Python wrapper of the SDL API). The code is intended to assist newcomers in gradually learning these libs.
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Moebius is a mud server, written in python using (currently) MySQL as a back-end. It's design goals are to be extensible without taking the engine down, to be distributable via the database, and to allow a complete python coding/learning env online. It
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Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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Think Python
Think Python is an interactive online learning environment for Python.
Think Python intends to be an interactive online learning environment for Python. It consists of two parts: A small IDE which is able to run your Python code in the browser without installing any plugins and an interactive training system which can contain explainations, questions and practical tasks. -
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chronos-bolt-base
Fast, accurate zero-shot time series forecasting with T5 encoder
... speed and memory efficiency—being up to 600 times faster than Chronos-Large—while outperforming various deep learning and statistical forecasting models in accuracy, even in zero-shot settings. Chronos-Bolt is ideal for scalable forecasting tasks and is compatible with SageMaker and AutoGluon. -
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t5-small
T5-Small: Lightweight text-to-text transformer for NLP tasks
.... It was pretrained on the C4 dataset using both unsupervised denoising and supervised learning on tasks like sentiment analysis, NLI, and QA. Despite its size, it performs competitively across 24 NLP benchmarks, making it a strong candidate for prototyping and fine-tuning. T5-Small is compatible with major deep learning frameworks including PyTorch, TensorFlow, JAX, and ONNX. The model is open-source under the Apache 2.0 license and has wide support across Hugging Face's ecosystem. -
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VocabTrainer is an freeware, open-source python-based system to aid in learning new languages. It is the ideal companion to a language class or course.
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chronos-bolt-small
Fast, efficient T5-based model for zero-shot time series forecasting
... probabilistic and point forecasting across diverse domains without prior exposure to target datasets. Benchmarking shows that even this small variant outperforms traditional statistical methods and many trained deep learning models. It is designed to be easily integrated into workflows using AutoGluon or deployed at scale on SageMaker. Chronos-Bolt is especially suitable for scalable forecasting tasks in production environments where speed, accuracy, and memory efficiency are critical. -
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Graphical score editor for contemporary dance. dansel intend to be used for learning and composing contemporary choreography.
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ddreditor (Digital Didatic Resource Editor) is a editor of Digital Didatic Resources (learning objects and more). It is implemented using Python and it´s GTK bindings and uses a docbook substed as it´s markup language.
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The learnbt is an open source learning bt protocol and c++ written and usable in C++. It is linux & unix platform software.
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The Local Content Server transforms Plone into a robust Learning Object Repository. It supports IMS content package transport, content preview, and object identification and registration.
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DeepSWE-Preview
State-of-the-art RL-trained coding agent for complex SWE tasks
DeepSWE-Preview is a 32.8B parameter open-source coding agent trained solely with reinforcement learning (RL) to perform complex software engineering (SWE) tasks. Built on top of Qwen3-32B, it achieves 59% accuracy on the SWE-Bench-Verified benchmark—currently the highest among open-weight models. The model navigates and edits large codebases using tools like a file editor, bash execution, and search, within the R2E-Gym environment. Its training emphasizes sparse reward signals, test-time... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
... for very long sequences. Trained using large-scale reinforcement learning on diverse tasks, it excels in mathematics, software engineering, agentic tool use, and long-context understanding benchmarks. It outperforms other open-weight models like DeepSeek R1 and Qwen3-235B on complex reasoning and coding challenges. MiniMax-M1 is available in two versions with 40K and 80K token thinking budgets, offering scalable performance based on your application needs. -
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Meta-Llama-3-8B-Instruct
Instruction-tuned 8B LLM by Meta for helpful, safe English dialogue
Meta-Llama-3-8B-Instruct is an instruction-tuned large language model from Meta’s Llama 3 family, optimized for safe and helpful English dialogue. It uses an autoregressive transformer architecture with Grouped-Query Attention (GQA) and supports an 8k token context length. Fine-tuned using supervised learning and reinforcement learning with human feedback (RLHF), the model achieves strong results on benchmarks like MMLU, GSM8K, and HumanEval. Trained on over 15 trillion tokens of publicly... -
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ERNIE-4.5-VL-28B-A3B-Paddle
Multimodal ERNIE 4.5 MoE model for image-text reasoning and chat
..., including Reinforcement Learning with Verifiable Rewards (RLVR), to enhance alignment and performance. Fine-tuned for real-world applications, it integrates language and vision through supervised learning, DPO, and UPO techniques. It supports long contexts up to 131,072 tokens and can be deployed using FastDeploy or the Hugging Face Transformers library. This version is ideal for developers needing high-performance, scalable multimodal capabilities in chat or image-based reasoning systems. -
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Llama-2-7b-chat-hf
Dialogue-optimized 7B language model for safe and helpful chatting
Llama-2-7b-chat-hf is a fine-tuned large language model developed by Meta, designed specifically for dialogue use cases. With 7 billion parameters and built on an optimized transformer architecture, it uses supervised fine-tuning and reinforcement learning with human feedback (RLHF) to enhance helpfulness, coherence, and safety. It outperforms most open-source chat models and rivals proprietary systems like ChatGPT in human evaluations. Trained on 2 trillion tokens of public text and over 1... -
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Llama-3.1-8B-Instruct
Multilingual 8B-parameter chat-optimized LLM fine-tuned by Meta
Llama-3.1-8B-Instruct is a multilingual, instruction-tuned language model developed by Meta, designed for high-quality dialogue generation across eight languages, including English, Spanish, French, German, Italian, Portuguese, Hindi, and Thai. It uses a transformer-based, autoregressive architecture with Grouped-Query Attention and supports a 128k token context window. The model was fine-tuned using a combination of supervised fine-tuning (SFT), reinforcement learning with human feedback (RLHF...
