11:48

The Building Blocks of Deep Learning

07:57

Deep Neural Network Validation

00:55

That's not supposed to happen!

17:04

4th Annual Krispy Kreme Challenge Fleet Feet Sports Bloomington IL

13:18

Multinomial Logistic Regression with Tensorflow

07:52

Convolutional Neural Networks in Tensorflow

05:01

Multilayer Perceptrons in TensorFlow

08:14

What's an MNIST

19:28

From the Perceptron to Deep Learning

16:54

Fleet Feet Bloomington KRISPY KREME CHALLENGE FUN RUN

08:43

Using Flask to serve a machine learning model as a RESTful webservice

11:49

Lambda Architecture in 10 minutes or less

09:30

Graph Theory - Medline 2

11:24

Graph Theory - Medline1

08:45

Using Graph Centrality on a list of citizens from Boston 1776

08:36

An Intro to Graph Centrality and it's uses

18:54

Advanced Validation

09:47

A simple python recommender

09:05

Finding the Perfect Scotch using K-Means Clustering

09:36

Introduction to K-Means Clustering

06:28

Using Naive Bayes for Sentiment Analysis

23:53

Full Titanic Example with Random Forest

12:33

Random Forest Algorithm And Parameters by Jason Sanchez

17:24

Decision Trees by Jason Sanchez

02:24

The Bootstrap by Jason Sanchez

06:58

Random Forest == Awesome by guest speaker Jason Sanchez

15:21

Logistic Regression Classifiers

05:47

Measuring Linear Regression Performance

10:23

Intro to Linear Regression for CS570

10:55

Using TF-IDF to convert unstructured text to useful features

14:34

Text Analytics - Latent Semantic Analysis

26:17

Introduction to Pandas with the Titanic Dataset

08:29

Handling Missing Values

07:29

Getting Around in Ipython Notebook

07:22

Measuring ML Model Performance

20:22

Machine Learning Overview

13:23

Data Science Lifecycle

01:25

CS 570: Data Science Essentials - Introduction