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03_gee_labs_dspg

Python Labs for the Data Science of Public Good

18s191

Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:

a-b_testing

List of A/B testing examples

analyzekge

Analyzing knowledge graph embedding methods, including TransE, DistMult, CP, SimplE, ComplEx, Quaternion

awesome-bigdata

A curated list of awesome big data frameworks, ressources and other awesomeness.

brand_sentiment_analysis_with_nlp

Using LSTM and GRU network to perform sentiment classification from Twitter data

calculating-distance-data-science-intro-000

calculating-distance-lab-data-science-intro-000

calculus-derivation-gradient-descent-data-science-intro-000

cnn-based-seismic-fault-prediction

Using Convolution Neural Network for Seismic Fault Mapping

cnn-for-asi

Tutorial: Convolutional Neural Networks for Automated Seismic Interpretation

customer-churn-project

This project covers an end-to-end machine learning cycle. You can examine the model development, interface, api and docker stages of the project.

cwd-benchmark-data

Data for the Chat With Your Data benchmark.

datacamp

code for DataCamp classes

datascience

Data Science in Julia course for JuliaAcademy.com, taught by Huda Nassar

derivative-rules-data-science-intro-000

dsc-accessing-data-with-pandas-lab

dsc-analyzing-macbeth-project-v2-1

dsc-bernoulli-and-binomial-distribution-lab

dsc-central-limit-theorem-lab

dsc-coefficient-of-determination-lab

dsc-combinations-lab

dsc-combining-dataframes-pandas-lab

dsc-complete-regression-lab

dsc-conditional-probability-lab

dsc-confidence-intervals-lab

dsc-correlation-covariance-lab

dsc-cumulative-distribution-function-lab

dsc-data-cleaning-project

dsc-data-visualization-with-pandas