6890 Open source projects that are alternatives of or similar to The Deep Learning With Keras Workshop

High-throughput gene to knowledge mapping through massive integration of public sequencing data.

A repo of sample data for our PyData Tutorial!

Instructions for reproducing the research described in the paper "Tempo Estimation for Music Loops and a Simple Confidence Measure"

Pytorch code for multi-Instance multi-label problem

(Winter 2015) Python for Data Mining mini-course.

ECON 5253: Data Science for Economists, University of Oklahoma (Spring 2019)

Overview of NLP tools and techniques in python

Code and visualizations for related/similar subreddits

Reliably download millions of images efficiently

My kaggle competition solution and notebook

Compilado de cursos y material de capacitación en herramientas de IA y DataScience.

PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

Chatbot based on Rasa Framework

支付宝 AR 红包 破解教程

Apache Spark - Turbofan Engine Degradation Simulation Data Set example in Apache Spark

tensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition

A collection of tutorials, demos, and use cases for IBM Data Science Experience http://datascience.ibm.com/

GeoPyTeR: Geographical Python Teaching Resource

https://www.kaggle.com/c/carvana-image-masking-challenge

Object detection useful tools for TensorFlow Object Detection API

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Kaggle Competition notebooks

Presentation and code from Cryptocurrency Technical Trading strategy meeting. Dec 7th 2017

QuAI is QNAP’s AI Developer Package, for data scientists and developers, to quickly build, train, optimize and deploy machine learning models, on top of QNAP NAS.

Time Series Anomaly Detection Toolkit

Talk at scipy 2018: Interactive 3d Visualization in Jupyter

Image clustering using the similarity algorithms: SIFT, SSIM, CW-SSIM, MSE

AI Generated Tees

Implementation of various generative models

When performing data science tasks, it's common to want to use data found on the internet. You'll usually be able to access this data in csv format, or via an Application Programming Interface (API). However, there are times when the data you want can only be accessed as part of a web page. In cases like this, you'll want to use a technique called web scraping to get the data from the web page into a format you can work with in your analysis.

Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.

Repository containing a dataSet and a python notebook to perform data analysis about workouts. The data was gathered from Health Graph API - Runkeeper

PyTorch code for Paper "Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational Inference"

Kaggle에서 진행하는 경진대회의 코드를 올려둔 공간입니다.

privacy

DeepLearning.AI TensorFlow Developer Professional Certificate Specialization

How to do data science with Optimus, Spark and Python.

Create HTML profiling reports from pandas DataFrame objects

使用Theano实现的一些RNN代码，包括最基本的RNN，LSTM，以及部分Attention模型，如论文MLSTM等

ML.NET Workshop to predict car sales prices

Interview = 简历指南 + LeetCode + Kaggle

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

Contains the code for my financial machine learning articles

Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

Learn Python for free using open-source notebooks in Hebrew.

Call of Duty World League Player Data

This repository contains easy SSD(Single Shot MultiBox Detector) implemented with Pytorch and is easy to read and learn

Implementation of Google's Inception + ResNet v2 architecture in Keras

A PyTorch Implementation of the paper - Choi, Woosung, et al. "Investigating u-nets with various intermediate blocks for spectrogram-based singing voice separation." 21th International Society for Music Information Retrieval Conference, ISMIR. 2020.

Introductory QMC teaching material for Python

Topic and material (if available) of the talks

This Contains Algorithms and codes for NLP, CV and deep learning basics and some advanced concepts

A fintech tutorial using Python

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]