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Codes For Audio Sentiment Analysis of Call Center Data
Example of plant image classification with a neural network built in numpy using data from https://www.kaggle.com/fpeccia/weed-detection-in-soybean-crops. Original source: https://www.kaggle.com/datduyn/2-layer-net-on-weeds-discriminant/
Example inspired from https://keon.io/deep-q-learning/ to gain a better understanding of deep-q-learning
Understanding emotions with Neural Networks (Python, Scikit-Learn, Keras) and the Ravdess dataset: 95% accuracy on the training set and 92% on the test set.
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Fashion MNIST GAN example, using tensorflow 2.0 + keras
Abstraction layer of the Native Instruments' Host Integration Agent API for the FL Studio MIDI Scripting API
Using linear regression model in python to predict fraud transactions
GPT-3: Language Models are Few-Shot Learners
Grok open release
Keras-stripe-auth-login-webapp incorporates image classification, user authentication, login functionality, and payment functionality. Heavily inspired by other great repositories, this is my meager attempt to piece them all together into something deployable with render.io
Community funded painting tool powering Kleki.com
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
Implementation of Particle-based Viscoelastic Fluid Simulation
Pneumonia Detection using inception v3, Ensure you have CUDA 10.0, CUDA Tookit, cuDNN SDK (>= 7.4.1) https://www.tensorflow.org/install/gpu#software_requirements
Simple image classifier web app that uses your webcam. Buttons A,B,C will capture a frame and add it to that classification group. Calibrate None should be used to establish a baseline (no objects present for classification)
Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
Stock forecasting using Linear Regression,Quadratic regression and KNN in a jupyter notebook
Cross-Platform Web-App for Sketching - based on Alchemy
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.