shubhampachori12110095 Goto Github PK

practical-pytorch

PyTorch tutorials demonstrating modern techniques with readable code

practical-reinforcement-learning

Practical​ Reinforcement Learning, published by Packt

practical-sentiment-analysis

Sentiment analysis by various methods and datasets.

practical_rl

A course in reinforcement learning in the wild

practical_seq2seq

A simple, minimal wrapper for tensorflow's seq2seq module, for experimenting with datasets rapidly

practicalai

A practical approach to machine learning →

practnlptools

Practical Natural Language Processing Tools for Humans. Dependency Parsing, Syntactic Constituent Parsing, Semantic Role Labeling, Named Entity Recognisation, Shallow chunking, Part of Speech Tagging, all in Python.

pratik-derin-ogrenme-uygulamalari

Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.

preciseroipooling

Precise RoI Pooling with coordinate gradient support, proposed in the paper "Acquisition of Localization Confidence for Accurate Object Detection" (https://arxiv.org/abs/1807.11590).

predict-financial-recession

The major goal of this project is to predict financial re- cession given the frequencies of the top 500 word stems in the reports of financial companies. After applying various learning models, we can see that the prediction of financial recession by the bag of words has an accuracy of more than 90%. Hence, there is indeed a correlation between the two. Moreover, we have compared different learning models (ensemble methods with Decision Tree, SVM, and KNN) with various parameters to find the best model with a relatively high average accuracy and low variance of accuracy by cross-validation on the training data set. In addition, we have also tried several pre-processing methods (tf-idf, feature selection, and centroid-based clustering) to improve the accuracy of the learning models. In the end, the best model is Gradient Boosting with Decision Tree using the pre-processed tf-idf data set.

predict_real_estate_prices

Predicting Amsterdam house / real estate prices (in Python) using Linear Regression, KNN-, Lasso-, Ridge-, Polynomial-, Support Vector (SVR)-, Decision Tree-, Random Forest-, and Neural Network MLP Regression.

prediction-flow

Deep-Learning based CTR models implemented by PyTorch

prediction_gan

PyTorch Impl. of Prediction Optimizer (to stabilize GAN training)

predictive-analytics-with-tensorflow

Predictive Analytics with TensorFlow, published by Packt

predictive-maintenance-using-lstm

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

predictive_modeling_price

Data Analysis and Machine Learning with Python: EDA with ECDF and Correlation analysis, Preprocessing and Feature engineering, L1 (Lasso) Regression and Random Forest Regressor with scikit-learn backed up by cross-validation, grid search and plots of feature importance.

predictron

Tensorflow implementation of "The Predictron: End-To-End Learning and Planning"

prednet

Code and models accompanying "Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning"

predrnn-pp

Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)

presgans

Prescribed Generative Adversarial Networks

pretrained-language-model

Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

pretrained-show-and-tell-model

This repository contains pretrained Show and Tell: A Neural Image Caption Generator implemented in Tensorflow.

prettytensor

Pretty Tensor: Fluent Networks in TensorFlow

pricegraph

Open code for PriceGraph

prml

PRML algorithms implemented in Python

prmlt

Matlab code for machine learning algorithms in book PRML

prnet

The source code of 'Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network'.

probabilistic-graphical-models-with-matlab

probabilistic-lexicon-classification