Search Results for "python data analysis" - Page 40
Sort By:
Showing 1214 open source projects for "python data analysis"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
SQLFlow
SQL compiler bridging databases and machine learning workflows
...By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. SQLFlow also supports model training, prediction, and explanation tasks, allowing data practitioners to work entirely within a familiar query interface. -
2
CommAI-env
A platform for developing AI systems
CommAI-env is an open research environment created by Facebook AI Research to advance studies in communication-based artificial intelligence. The project provides a flexible framework for testing and developing interactive learning agents that can acquire and use natural language to accomplish complex tasks. Inspired by the goals of Artificial General Intelligence (AGI), the CommAI environment focuses on enabling machines to learn not just from labeled data, but through communication and... -
3
Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained... -
4
Multilingual Speech Synthesis
An implementation of Tacotron 2 that supports multilingual experiments
This repository provides synthesized samples, training and evaluation data, source code, and parameters for the paper One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech. It contains an implementation of Tacotron 2 that supports multilingual experiments and that implements different approaches to encoder parameter sharing. It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice... -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
5
StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. ... -
6
VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
VideoPose3D is a deep learning framework that reconstructs 3D human poses from 2D keypoint sequences extracted from videos. It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. By using only 2D... -
7
NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional... -
8
Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more. -
9
HyperGAN
Composable GAN framework with api and user interface
A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
10
Delta ML
Deep learning based natural language and speech processing platform
...DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train, develop, and deploy NLP and/or speech models. Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. ... -
11
TFKit
Handling multiple nlp task in one pipeline
TFKit is a tool kit mainly for language generation. It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the... -
12
Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
13
NSFW Detection Machine Learning Model
Keras model of NSFW detector
Keras model of NSFW detector, NSFW Detection Machine Learning Model. -
14
COCO Annotator
Web-based image segmentation tool for object detection & localization
COCO Annotator is a web-based image annotation tool designed for versatility and efficiently label images to create training data for image localization and object detection. It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, label objects with disconnected visible parts, and efficiently store and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and... -
15
fastText
Library for fast text classification and representation
...Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels). -
16
ModelDB
Open Source ML Model Versioning, Metadata, and Experiment Management
An open-source system for Machine Learning model versioning, metadata, and experiment management. ModelDB is an open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle. -
17
SINGA
A distributed deep learning platform
Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models. Various example deep learning models are provided in SINGA repo on Github and on Google Colab. SINGA supports data parallel training across multiple GPUs (on a single node or across different nodes). SINGA supports various popular optimizers including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad, etc. SINGA records the computation graph and... -
18
FastoCloud PRO
IPTV/NVR/CCTV/Video cloud https://fastocloud.com
IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ... -
19
NLP Best Practices
Natural Language Processing Best Practices & Examples
In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive business adoption of artificial intelligence (AI) solutions. In the last few years, researchers have been applying newer deep learning methods to NLP. Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and... -
20
TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
21
awesome-TS-anomaly-detection
List of tools & datasets for anomaly detection on time-series data
All lists are in alphabetical order. In the lists, maintained projects are prioritized vs not mantained. A repository is considered "not maintained" if the latest commit is > 1 year old, or explicitly mentioned by the authors. -
22
Python Machine Learning
The "Python Machine Learning (2nd edition)" book code repository
...Each chapter has Jupyter notebooks and Python scripts that replicate the examples in the book, allowing readers to run, inspect, and tweak code directly as they follow material. The structure also includes errata documentation and assets (images) that appear in the printed edition, providing a rich supplement to learning. The repository is suitable both for classroom use and for self-study, as well as being a go-to reference for data scientists revisiting techniques. -
23
VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies... -
24
Aida Lib
Aida is a language agnostic library for text generation
Aida is a language-agnostic library for text generation. When using Aida, first you compose a tree of operations on your text that includes conditions via branches and other control flow. Later, you fill the tree with data and render the text. A building block is a variable class: Var. Use it to represent a value that you want to control later. A variable can hold numbers (e.g. float, int) or strings. You can create branches and complex logic with Branch. The context, represented by the... -
25
CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic...
