AnnOl1's Stars
facebookresearch/EmpatheticDialogues
Dialogue model that produces empathetic responses when trained on the EmpatheticDialogues dataset.
deshpandenu/Time-Series-Forecasting-of-Amazon-Stock-Prices-using-Neural-Networks-LSTM-and-GAN-
Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.
Mathanraj-Sharma/sample-for-medium-article
Contains sample codes for various python tasks
EvgeniiMunin/ctr_project
ancatmara/data-science-nlp
NLP Section of the Data Science course, NRU HSE
nlp-with-transformers/notebooks
Jupyter notebooks for the Natural Language Processing with Transformers book
microsoft/CodeBERT
CodeBERT
JesusFreke/smali
smali/baksmali
liuhh02/stanford-algorithms-specialization
Problem Set and Programming Assignment Solutions to Stanford University's Algorithms Specialization on Coursera & edX
rvarun7777/Graph-Search--Shortest-Paths--and-Data-Structures
Graph Search, Shortest Paths, and Data Structures
prabhnoor0212/Siamese-Network-Text-Similarity
This is a basic Siamese network for checking similarity of texts. The example used is of Kaggle Question Pair Similarity Datset.
trainindata/deploying-machine-learning-models
Code for the online course "Deployment of Machine Learning Models"
egonSchiele/grokking_algorithms
Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)
dustinsgoodman/coursera_algorithms
Personal files related to Coursera Algorithms course
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
ravising-h/Urbansound8k
Sound Classification using Librosa, ffmpeg, CNN, Keras, XGBOOST, Random Forest.
AnnOl1/XAI-for-speech-recognition
Yorko/mlcourse.ai
Open Machine Learning Course
abaranovskis-redsamurai/automation-repo
Machine learning and process automation
a1ip/Abbakumov
Анализ данных на Python в примерах и задачах
pandas-ml/pandas-ml
pandas, scikit-learn, xgboost and seaborn integration
jrjohansson/scientific-python-lectures
Lectures on scientific computing with python, as IPython notebooks.
esokolov/ml-course-hse
Машинное обучение на ФКН ВШЭ
esokolov/ml-course-msu
Lecture notes and code for Machine Learning practical course on CMC MSU
shap/shap
A game theoretic approach to explain the output of any machine learning model.
suinleelab/treeexplainer-study
Code and documentation for experiments in the TreeExplainer paper
EthicalML/xai
XAI - An eXplainability toolbox for machine learning
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
ModelOriented/DrWhy
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
marcoancona/DeepExplain
A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)