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capsule_networks

This is the code for "Capsule Networks: An Improvement to Convolutional Networks" by Siraj Raval on Youtube

code_snippets

concept-parser

concept parser

content

Official content for Harvard CS109

convolutional_neural_network

This is the code for "Convolutional Neural Networks - The Math of Intelligence (Week 4)" By Siraj Raval on Youtube

dbda-python

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

embedded-systems

Embedded systems

freshpandas

jupyter

Jupyter metapackage for installation, docs and chat

labeled-tweet-generator

Search for tweets and download the data labeled with its polarity in CSV format

machinelearningbasics

My adopted notebooks of machine learning basics. Codes from llSourcell, Sentdex and other public GitHub users can be used.

py-corenlp

Python wrapper for Stanford CoreNLP

python-nltk-exercise---sentiwordnet-scoring

python-NLP-Simple Sentiment Analysis

python-programming-exercises

100+ Python challenging programming exercises

quick_test

random_forests

This is the code for "Random Forests - The Math of Intelligence (Week 7)" By Siraj Raval on Youtube

regression-stock-prediction

Predicting Google’s stock price using regression

sentic

Library for Sentic and Semantic Analysis

senticnet-sentiment-analysis

This repository contains an application for performing basic sentiment analysis using the SenticNet sentiment lexicon. Developed in Python 2.7

senticnetapi

Simple API to use SenticNet 5

smai-stock-prediction

Implemented a system that analyses previous stock data of various companies, processes Time-Series data and aims to forecast the trends of stock in near future. Prediction is done using Supervised Learning Methods. (SVM ,Neural network)

sqlzoo

Solution for the SQL basics tutorial questions http://sqlzoo.net

stock-er

💰🤑Predictive model for stock prices🤑💰

stock-market-prediction-using-natural-language-processing

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

tensorflow_demo

Tensorflow Demo for my TF in 5 Min Video on Youtube

url_shortener

Данная репозитория создана для размещения решения задания по созданию интерфейса для сокращения URL ссылок.