bryan-dicarlo Goto Github PK

-boston-housing-data-project

ab-testing-lab

accessing-data-within-pandas-lab

advertising-data_logisticregression_ml

Logistic Regression and ML modeling of some "not' real Advertising Data

applying-gradient-descent-data-science-intro-000

applying-gradient-descent-lab

applying-gradient-descent-lab-data-science-intro-000

applying-nearest-neighbors-data-science-intro-000

bank-account-class-object

basic-movie-recommender-system

Develop basic recommendation systems using Python and pandas. We will focus on providing a basic recommendation system by suggesting items that are most similar to a particular item, in this case, movies. this is not a true robust recommendation system. Pretty basic. it just tells you what movies/items are most similar to your movie choice

basic-time-series-models-lab

bayes-theorem-lab

bd_tensorflow-with-estimators_iris-data-set

Here we use Tensorflow with estimators to predict the species of flower from the IRIS data set. The IRIS data set is a data set containing four measurements from three different species of the iris flower. The four measurements wre taken from 50 different flowers in each of the three different species. We will use Tensorflow with estimators to train a model and then predict the species of flower from the training data.

bernoulli-and-binomial-distribution-lab

bias-variance-trade-off-lab

black_jack

breast-cancer-diagnosis-with-naive-bayes-classifier-lab

bryan-dicarlo-mod-1-final-project

bryan-dicarlo-mod-1-final-project_v3

bryan-dicarlo-mod1-final-project

bryan-dicarlo-mod1-final-project_v4

bryan-dicarlo.github.io

building-a-cnn-from-scratch

building-an-object-oriented-simulation-lab

building-an-svm-using-scikit-learn

calculating-distance-data-science-intro-000

calculating-distance-lab-data-science-intro-000

calculating-lines-data-science-intro-000

calculus-derivation-gradient-descent-data-science-intro-000

capstone-project

In Depth NBA Shots Log Analysis