serenamm Goto Github PK

backtrader

Python Backtesting library for trading strategies

bc-election-analysis-may2017

Sentiment analysis using VADER in Python of the BC Provincial Election in May 2017

char-rnn-tensorflow

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow

clv

customer lifetime value calculation

cyberbert

cyberBERT

deep-learning-with-python

Example projects I completed to understand Deep Learning techniques with Tensorflow.

django-pwa

Looks like an app, feels like an app, but IS NOT an app.

django-simple-pwa

PWA is a simple Django app to develope and deploy a Progressive Web Application.

english-to-cantonese-jyutping-translator-hack

Translate from English to Cantonese Jyutping (Romanization) without needing any training data

friendlyveg

friendly veg website

guru-ratings

A system to verify the accuracy of public forecasts of stocks by "gurus" or other individuals who like to post online.

kaggle-schizophrenia-may-2017

Diagnosing patients with schizophrenia

lifestylecoopwebsite

A Jekyll version of the Clean Blog theme by Start Bootstrap

mlops-workshop

AISC mlops workshop Oct 2019

pirateradio

Raspberry Pi Automated FM Radio Script

ranking

Learning to Rank in TensorFlow

resume-matcher--find-a-job-on-glassdoor

Match your resume to available job postings on Glassdoor.ca

s-and-p-500-companies

List of companies in the S&P 500 together with associated financials

serenamm.github.io

speaking

Slides for talks I've done

toronto_bikeshare

analysis of Toronto Bike Share data

treat-jekyll-template

:cake: Food/baking blog template for Jekyll

trudeau-twitter-sentiment-analysis-oct-2017

Trudeau Twitter Sentiment Analysis

vancouver-public-art-jupyter-notebook

Exploration of public art sites in Vancouver

vegetarian-or-not

Using Instacart's 3 Million Orders dataset to classify someone as vegetarian or not

vso-churn

Churn prediction for the Vancouver Symphony Orchestra

wine_exploration

Exploring wine data set, and predicting prices with linear models