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analyzing-public-transit

dsi-project-07

face_generation

image-classification

In this project, we'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. we'll preprocess the images, then train a convolutional neural network on all the samples. We'll get to apply what you learned and build a convolutional, max pooling, dropout, and fully connected layers.

image-classification-using-vggnet

Most of the time you won't want to train a whole convolutional network yourself. Modern ConvNets training on huge datasets like ImageNet take weeks on multiple GPUs. Instead, most people use a pretrained network either as a fixed feature extractor, or as an initial network to fine tune. In this notebook, you'll be using VGGNet trained on the ImageNet dataset as a feature extractor.

indeed-salary-prediction

In this project, we are going to collect salary information on data science jobs in a variety of markets. Then using the location, title, and summary of the job, we will attempt to predict a corresponding salary for that job. While most listings DO NOT come with salary information, being to able extrapolate or predict the expected salaries for other listings will be extremely useful for negotiations.

iowa-state-sales-prediction

Develope a analytics report for the Iowa State legislature regarding liquor sales who are considering changes to sales tax rates. Provide current liquor sales by county and projections for the rest of the year.

koalas

Koalas: pandas API on Apache Spark

language-translation

In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset of English and French sentences that can translate new sentences from English to French.

machine-learning-pipelines

mlflow

Open source platform for the machine learning lifecycle

part-02

part-05

py_entitymatching

sales-prediction-neural-network-numpy

In this project, we'll build our first neural network and use it to predict daily bike rental ridership.

semantic-search-engine-wikipedia

Built a semantic search engine that returns top five related articles text snippets and full text from the top related article on Wikipedia, and a predictive model that categorize new articles with an accuracy score of 98%.

statistical-analysis-matplotlib-python

titanic-vs-lusitania

tv-script-generation-rnn

In this project, we'll generate our own Simpsons TV scripts using RNNs. We'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Network we'll build will generate a new TV script for a scene at Moe's Tavern.