Fecon235Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Stars: ✭ 708 (+574.29%)
EconmlALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Stars: ✭ 1,238 (+1079.05%)
FmaFMA: A Dataset For Music Analysis
Stars: ✭ 1,391 (+1224.76%)
GspanPython implementation of frequent subgraph mining algorithm gSpan. Directed graphs are supported.
Stars: ✭ 103 (-1.9%)
100 Pandas Puzzles100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
Stars: ✭ 1,382 (+1216.19%)
NotebooksMy IPython Notebooks
Stars: ✭ 103 (-1.9%)
DmmDeep Markov Models
Stars: ✭ 103 (-1.9%)
Av exampleExamples on how to use the alpha vantage library
Stars: ✭ 103 (-1.9%)
Gen QuickstartDocker file for building Gen and Jupyter notebooks for tutorials and case studies
Stars: ✭ 104 (-0.95%)
Bert Loves Chemistrybert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Stars: ✭ 103 (-1.9%)
Face ClassificationFace model to classify gender and race. Trained on LFWA+ Dataset.
Stars: ✭ 104 (-0.95%)
SurvivalstanLibrary of Stan Models for Survival Analysis
Stars: ✭ 103 (-1.9%)
DeepaiDetection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
Stars: ✭ 104 (-0.95%)
How to make an image classifierThis is the code for the "How to Make an Image Classifier" - Intro to Deep Learning #6 by Siraj Raval on Youtube
Stars: ✭ 103 (-1.9%)
K means clusteringThis is the code for "K-Means Clustering - The Math of Intelligence (Week 3)" By SIraj Raval on Youtube
Stars: ✭ 103 (-1.9%)
Unet Segmentation In Keras TensorflowUNet is a fully convolutional network(FCN) that does image segmentation. Its goal is to predict each pixel's class. It is built upon the FCN and modified in a way that it yields better segmentation in medical imaging.
Stars: ✭ 105 (+0%)
DlnotebooksINACTIVE - please go to https://gitlab.com/juliensimon/dlnotebooks
Stars: ✭ 103 (-1.9%)
YaboxYet another black-box optimization library for Python
Stars: ✭ 103 (-1.9%)
Sigmoidal aiTutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal
Stars: ✭ 103 (-1.9%)
BoxdetectionA Box detection algorithm for any image containing boxes.
Stars: ✭ 104 (-0.95%)
Ec2 Spot WorkshopsCollection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/
Stars: ✭ 104 (-0.95%)
Kaggle Ds Bowl 2018 BaselineFull train/inference/submission pipeline adapted to the competition from https://github.com/matterport/Mask_RCNN
Stars: ✭ 105 (+0%)
CenpyExplore and download data from Census APIs
Stars: ✭ 104 (-0.95%)
Nlp essentialsEssential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies
Stars: ✭ 104 (-0.95%)
Ml4music WorkshopMachine Learning for Music and Sound Synthesis workshop
Stars: ✭ 105 (+0%)
Covid 19A collection of work related to COVID-19
Stars: ✭ 1,394 (+1227.62%)
PytorchnlpbookCode and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info
Stars: ✭ 1,390 (+1223.81%)
SatimgSatellite data processing experiments
Stars: ✭ 104 (-0.95%)
Summerschool2016Montréal Deep Learning Summer School 2016 material
Stars: ✭ 103 (-1.9%)
Pixel2style2pixelOfficial Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation"
Stars: ✭ 1,395 (+1228.57%)
DndtDeep Neural Decision Trees
Stars: ✭ 103 (-1.9%)
MatgenbJupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.
Stars: ✭ 103 (-1.9%)
Sharing isl pythonAn Introduction to Statistical Learning with Applications in PYTHON
Stars: ✭ 105 (+0%)
Ai机器学习、深度学习、自然语言处理、计算机视觉等AI领域相关技术的算法推导及应用
Stars: ✭ 103 (-1.9%)
Tf objectdetection apiTutorial on how to create your own object detection dataset and train using TensorFlow's API
Stars: ✭ 105 (+0%)
SophiaNeural networks from scratch
Stars: ✭ 103 (-1.9%)
Ossdc VisionbasedaccDiscuss requirments and develop code for #1-mvp-vbacc MVP (see also this channel on ossdc.org Slack)
Stars: ✭ 104 (-0.95%)
Lt GeeGoogle Earth Engine implementation of the LandTrendr spectral-temporal segmentation algorithm. For documentation see:
Stars: ✭ 103 (-1.9%)
ManipulationCourse notes for MIT manipulation class
Stars: ✭ 105 (+0%)
Personlab Tfimplementation of PersonLab(https://arxiv.org/abs/1803.08225) using TF-slim
Stars: ✭ 103 (-1.9%)
Practical Ml W PythonSource code for 'Practical Machine Learning with Python' by Dipanjan Sarkar, Raghav Bali, and Tushar Sharma
Stars: ✭ 104 (-0.95%)
Anomaly DetectionAnomaly detection algorithm implementation in Python
Stars: ✭ 105 (+0%)
How To Generate Art DemoThis is the code for "How to Generate Art - Intro to Deep Learning #8' by Siraj Raval on YouTube
Stars: ✭ 105 (+0%)