1 of 14

Data Analytics and AI

SLIDES BY:

RODRIGO RENE RAI MUNOZ ABUJDER

2 of 14

Data Analytics and AI�A Quick Introduction

Made By: Rodrigo Rene Rai Munoz Abujder

​

3 of 14

What is Data Analytics and AI ?

Data Analytics is the practice of quality and quantity-based techniques used to identify and analyze particular data patterns.

​

Artificial Intelligence, or AI is the practice of designing autonomous computer systems capable of Data Analytics.

​

What’s different?

Data Analytics involves modeling the data directly, while AI is about modeling the data indirectly, or teaching the computer how to do it.

4 of 14

Explaining Data Analytics

Like a climbing a mountain, Data Analytics has higher, more difficult regions to reach before getting to the top!

​

Yet, the higher you go, the more rewarding is the model to your data!

​

​

Difficulty

Rewards

​

5 of 14

How does Data Analytics look?

6 of 14

Explaining AI

AI is arguably split these 3 regions, each with their own field of study.

​

Machine Learning and Bioinspired Computation, utilize, in some form, techniques derived from the older study of Statistics and Optimization

Field of AI focused on using bio-processes such as mutation, or evolution to derive optimal results using data, controlled randomness, and iterations

Field of AI focused on designing data architectures capable of learning data-driven solutions

Field of AI focused on organizing, analyzing, optimizing, and interpreting data and solutions

7 of 14

How does AI look like?

Machine Learning

Demo: Recognizing Digits

(Demos embedded to images

ctrl + click to see!)

Bio-Inspired Computation:

Learning How to Walk

Statistics and Optimization:

Bus Traffic

8 of 14

Data and Challenges are Growing Really Fast!

9 of 14

Small Exercise!

  1. Make a Group or Pair up with others!

​

  • What problem you want to solve? Why do you think its important?

​

  • What type of data would you need? (i.e. Images, sound, etc.)Where/how much do you think you can get?

​

  • What area of data analysis or AI do you think it needs?

​

  • How do you plan to solve it using your data?

​

  • Present it to the Class!

​

​

10 of 14

Summary/ Resources

Having been introduced to a portion of Data Analysis and AI, hopefully, you may be interested on starting your journey! Here are some recommendations to start of with, if you’re interested in starting!:

​

​

  • NASA Goddard Space Flight Center Python Bootcamp 2016

https://github.com/JulesKouatchou/PBC2016/wiki/PBC2016-Agenda

2017: https://github.com/edmondb/gsfcbootcamp/wiki

​

  • Building a neural network from scratch

http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/

​

11 of 14

THANK YOU and Best of Luck!

12 of 14

Extra Slides

13 of 14

Types of Data Analytics

Like a mountain, Data Analytics has higher, more difficult regions to reach before getting to the top!

​

​

Linear & Logistic Regression

​

Discrete Choice Models

​

Time Series models (ARIMA)

​

Classification and Regression Trees (CARDT)

14 of 14

Explaining AI

Machine Learning

Deep Learning

Deep Reinforcement Learning

Bioinspired Computation

Genetic Algorithms

Evolutionary Methods

Statistics and Optimization

AI is arguably split into 3 Regions:

  1. Machine Learning
  2. Bioinspired Algorithms
  3. Statistics And Optimization

in which both ML and BA, take some inspiration from techniques in Stats and Optimization.

​