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advancedbasesas

Repo holding some work done in SAS for my reference. It is based on assignments and solutions developed based on the assignments. Assignment is a small use case.

banditalgorithm

Multi Arm Bandits

codemixed-hinglish

Contains artifacts for training few architecture of neural networks for classifying code mixed Hindi and English (Hinglish) tweets into 3 classes - Offensive, Hateful and Non offensive.

cs224n-nlp

deepnets

deeptriage

econml

ALICE (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.

finitemixturemodels

gams_semiparametricregression

ggplot2

Ggplot2 exploration

loglinear_glm_categoricaldatamodelling

methodsinstat2-advancedstats

multivariate-statistics

nlp-parkinglot

regression-analysis---linear-models-and-theory

repos

sampling-survey-designs

statistical-methods

statisticaldistributions

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

sudoku

tensorflows

textmining

timeseries