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spark-syntax

This is an open repo of all the best practices of writing PySpark that I have learnt from working with the Framework.

springchat

chatbot with spring and admin space for update knowledge

sql---cours-complets-et-tp-avec-correction

stanford-cs-221-artificial-intelligence

stanford-cs-229-machine-learning

stanford-cs-230-deep-learning

stockmarketanalysis

Using the power of Big Data Tools to analyze Stock Market

stocks-analysis

subtitle-downloader-by-python

Download Movies/TV Shows subtitles with ease using this python Script

superbe-data-collection

An index of all open-source data

team-predictions

Predicting an IPL ALL Stars team based on past performance of Players.

telecommunication-customer-base

Imagine a telecommunications provider has segmented its customer base by service usage patterns, categorizing the customers into four groups. If demographic data can be used to predict group membership, the company can customize offers for individual prospective customers. It is a classification problem. That is, given the dataset, with predefined labels, we need to build a model to be used to predict class of a new or unknown case. The example focuses on using demographic data, such as region, age, and marital, to predict usage patterns. The target field, called custcat, has four possible values that correspond to the four customer groups, as follows: 1- Basic Service 2- E-Service 3- Plus Service 4- Total Service Our objective is to build a classifier, to predict the class of unknown cases. We will use a specific type of classification called K nearest neighbour.

telecommunications-company-analyst-prediction-project

A telecommunications company is concerned about the number of customers leaving their land-line business for cable competitors. They need to understand who is leaving. Imagine that you are an analyst at this company and you have to find out who is leaving and why.

tensorflow-chatbot-chinese

網頁聊天機器人 | tensorflow implementation of seq2seq model with bahdanau attention and Word2Vec pretrained embedding

tensorflow-object-detection-api-tutorial-train-multiple-objects-windows-10

How to train a TensorFlow Object Detection Classifier for multiple object detection on Windows

tensorflow-without-a-phd

A crash course in six episodes for software developers who want to become machine learning practitioners.

tesseract---ocr

Tesseract is an open source text recognizer (OCR) Engine using which we can extract printed text from images. It supports a wide variety of languages

testgit

text-classification-with-movies-reviews

This project classifies movie reviews as positive or negative using the text of the review. This is an example of binary—or two-class—classification, an important and widely applicable kind of machine learning problem. We'll use the IMDB dataset that contains the text of 50,000 movie reviews from the Internet Movie Database. These are split into 25,000 reviews for training and 25,000 reviews for testing. The training and testing sets are balanced, meaning they contain an equal number of positive and negative reviews.

text-generation-gan

Conditional SeqGAN for generating text conditioned on certain sentiment. Stanford Sentiment Treebank. CS 224U Final Project

text_classification

all kinds of text classificaiton models and more with deep learning

text_generators

Python code for building a text generator using LSTMs.

textblob-sentiment-analysis

Simple example of using TextBlob to perform sentiment analysis

textrecognitiondatagenerator

A synthetic data generator for text recognition

texygen

A text generation benchmarking platform

tf_examples

TensorFlow and Scikit Flow examples

tfidfvectorizer

TF-IDF based system which uploads docs and help search documents faster

tp1_gb

tpu

Reference models and tools for Cloud TPUs.

tutorial-ubuntu-18.04-install-nvidia-driver-and-cuda-and-cudnn-and-build-tensorflow-for-gpu

Ubuntu 18.04 How to install Nvidia driver + CUDA + CUDNN + build tensorflow for gpu step by step command line