Pinned Repositories
1stPrimaryDebateNight2020
Analysis of the Twitter conversation around the 2020 Democratic presidential primary candidates from the first debate
3-speculative-markhov
Markhov chain twitter bot who likes to pitch speculative fiction
Billboard-Top-100-EDA
Exploratory data analysis of the recent Billboard Top 100 Artists using Spotify
BoardGameRecommender
TCF Science Fair: From a set of board games and/or mechanics create a recommendation of other board games
Data_Engineering_Nanodegree
Coursework for Udacity's Data Engineering Nanodegree
graph-of-thrones
Graph Network lecture developed for Flatiron School's Data Science program
language-in-politics
Analysis of US Congress 115 (2017-2018) using data on proposed Bills and tweets of Representatives.
Primary-Candidate-Analysis
Create, curate and analyze a collection of tweets related to the Democratic primary candidates for the 2020 US Presidential election.
Sentimental
Sentiment and statistical analysis of twitter data
Troll_Tweets
danjizquierdo's Repositories
danjizquierdo/dsc-3-31-06-decision-tree-scikitlearn-codealong-nyc-ds-career-012819
danjizquierdo/dsc-3-31-04-entropy-information-gain-nyc-ds-career-012819
danjizquierdo/dsc-3-30-06-coding-logistic-regression-from-scratch-nyc-ds-career-012819
danjizquierdo/dsc-3-31-03-introduction-to-decision-trees-nyc-ds-career-012819
danjizquierdo/dsc-2-19-07-poisson-distribution-nyc-ds-career-012819
danjizquierdo/dsc-3-31-02-introduction-to-PAC-learning-theory-nyc-ds-career-012819
danjizquierdo/dsc-3-27-11-knn-with-sklearn-nyc-ds-career-012819
danjizquierdo/dsc-3-31-13-section-recap-nyc-ds-career-012819
danjizquierdo/dsc-2-13-15-linalg-regression-lab-nyc-ds-career-012819
danjizquierdo/dsc-3-29-11-class-imbalance-problems-lab-nyc-ds-career-012819
danjizquierdo/dsc-3-29-10-class-imbalance-problems-nyc-ds-career-012819
danjizquierdo/dsc-2-14-12-gradient-descent-step-sizes-lab-nyc-ds-career-012819
danjizquierdo/dsc-2-14-11-gradient-descent-step-sizes-nyc-ds-career-012819
danjizquierdo/dsc-3-29-06-evaluating-logistic-regression-models-lab-nyc-ds-career-012819
danjizquierdo/dsc-git-clean-notebook-supplemental
danjizquierdo/dsc-3-29-05-fitting-a-logistic-regression-model-lab2-nyc-ds-career-012819
danjizquierdo/dsc-3-29-04-logistic-regression-in-scikit-learn-nyc-ds-career-012819
danjizquierdo/dsc-3-29-03-fitting-a-logistic-regression-model-lab-nyc-ds-career-012819
danjizquierdo/dsc-3-29-02-linear-to-logistic-regression-nyc-ds-career-012819
danjizquierdo/dsc-2-14-16-applying-gradient-descent-lab-nyc-ds-career-012819
danjizquierdo/dsc-2-31-01-introduction-nyc-ds-career-012819
danjizquierdo/dsc-2-14-15-gradient-to-cost-function-nyc-ds-career-012819
danjizquierdo/dsc-2-14-14-the-gradient-in-gradient-descent-nyc-ds-career-012819
danjizquierdo/dsc-2-14-04-introduction-to-derivatives-lab-nyc-ds-career-012819
danjizquierdo/dsc-2-14-03-introduction-to-derivatives-nyc-ds-career-012819
danjizquierdo/dsc-2-14-13-gradient-descent-in-3d-nyc-ds-career-012819
danjizquierdo/dsc-2-14-10-introduction-to-gradient-descent-nyc-ds-career-012819
danjizquierdo/dsc-2-14-09-derivatives-conclusion-nyc-ds-career-012819
danjizquierdo/dsc-2-14-07-rules-for-derivatives-lab-nyc-ds-career-012819
danjizquierdo/dsc-2-14-06-rules-for-derivatives-nyc-ds-career-012819