July Meetup

## Schedule

• Introduction (15 min)
• Understand the Machine learning concepts behind Chatbots
  (25 min + 5min)
• Entering the world of Serious Games with Python (25 min + 5 min)
• Networking Tea Break (30 min)
• Building Robust ML models against Adversarial Attacks using Python libraries (25 min + 5 min)
• Practical introduction to Graph DBs, Graph Traversals in Python (25 min + 5 min)

## Building Robust ML models against Adversarial Attacks using Python libraries
Speaker: Deya Chatterjee and Drishti

As machine learning & deep learning progresses rapidly, there is also an increasingly bigger concern about the privacy and security issues it entails. One of the most relevant problems in this regard is adversarial attacks that can "fool" a neural network and cause it to misclassify.

In this talk, we will delve deep into less-heard-of Python libraries (like Cleverhans and Foolbox) that are very important to tackle such adversarial attacks. We will show how these attacks a) compromise confidential and private data and b) fool neural networks to make wrong predictions, and also demonstrate with code possible attack defenses.

Talk sections:

1. What are adversarial examples; how they become adversarial attacks
2. types & real usecases
3. Intro to Cleverhans (attacks + defenses)
4. Demo of code (medical imaging)
5. Other libs, research trends
6. Q&A

## Entering the world of Serious Games with Python

Speaker: Harshinee

This talk will include the following: Introduction to Serious gaming, Game development phases for serious gaming, current examples, how does PyGame come into the discussion, how to use PyGame to develop a serious game

## Understand the Machine learning concepts behind Chatbots

Speaker: Bhavani Ravi

Have you ever tried building a chatbot? You would definitely start with Dialogflow or IBM Watson or any chatbot framework from these tech giants. As you start building you be curious to understand what’s happening underneath these engines. When the use case hit the real world you will find the importance of understanding these inner workings.

In this talk, we will open the hood of an open-source chatbot framework RasaNLU and understand the components involved and how they contribute to building a chatbot

## Practical introduction to Graph DBs, Graph Traversals in Python

Speaker: Srimathi

Graph databases are purpose-built to store and navigate relationships. In this talk, we will explore ways for a graph in a graph database that can be traversed along specific edge types, or across the entire graph. Apache TinkerPop™ is a graph computing framework that enables users to succinctly express complex traversals on (or queries of) their application’s property graph. Gremlin-Python implements Gremlin within the Python language. The talk itself will have the following sections:

1. What are Graph Databases
2. Property Graph - with Example Dataset
3. Tinkerpop & Gremlin
4. Patterns and writing queries using Python - Demonstrate some complicated queries
5. Graph DB Uses

## Speak at Chennaipy

If you are interested in doing a talk (20 min slot), please add a comment with your talk title and talk description.