Title

Rulette - A simple and versatile rule engine

Description

Rulette is an open source rule engine that I implemented some time ago. It is a lightweight rule definition, persistence, and evaluation library that covers most types of business rule management scenarios with extreme ease of setup and use. The talk will cover the motivation in building, design details, and a case study of how Rulette can be used for a real life use-case.

Duration

• 30 min
• 45 min

Audience

The talk is suitable for all levels, and especially useful for developers working on system which has lots of variant behaviour depending on dynamic input.

Outline

• What are rule engines and why we should use them.
• Why another rule engine (aka why you don't really need all that power)
• Rulette design and internal details
• Case Study

Additional notes

Rulete Repository - https://github.com/kislayverma/Rulette

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Title

Linkerd: Ultralight Service Mesh for Kubernetes

Description

In this session we will look into what is a Service Mesh and how we can leverage Linkerd to achieve Observability, Reliability and Security without any code change.

Duration

• 30 min
• [x ] 45 min

Audience

Service Mesh is an advanced Side Car pattern. However if you know what is Kubernetes and how you can deploy applications on K8s it should suffice.

Outline

Agenda:

• Kubernetes in brief (with architecture if required)
• What is Service Mesh?
• Why Service Mesh?
• What is Linkerd?
• Demo

Additional notes

I'm Ajay. I'm a Polyglot Programmer, Solutions Architect at JP Morgan Chase - Profile.
As a hobby, I have been creating educational videos on new Technology trends with hands-on examples in the Youtube Channel - TechPrimers for the last 3 years.

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Title

Title of the proposal, no buzz words!

Airflow - 0 to DAG

Description

We'll go through an introduction to Airflow and finish up by writing a simple DAG.
This is an introductory talk to using Airflow in your data workflows.

Duration

• 30 min
• 45 min

Audience

Mention the prerequisites for your talk. Additionally, mention if the talk is for a beginner, intermediate or advanced audience.

Beginners - Intermediate

Outline

A detailed outline for your talk. The more detailed the better. (1000 words)

WIP

Additional notes

You personal details, links to previous talks, etc.

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Slides: https://github.com/kkm24132/BRUG/blob/master/DeepLearning_using_R.pdf

Should I submit a PR?

Title

Dealing With Class Imbalance

Description

Skewed datasets are not uncommon. And they are tough to handle. Usual classification models and techniques often fail miserably when presented with such a problem. We discuss right from the basics of what class imbalance means to how we can overcome it, using various algorithms and some subtle techniques. We also discuss details of how to evaluate our efforts and some small but crucial things that must be taken care of.

Duration

30 min

Audience

The talk does require beginner to intermediate machine learning knowledge. However, the overall learning of the talk would still be understandable to someone who has never explicitly practiced machine learning before.

Outline

The talk has the following sections-

1. What is Class Imbalance?
   Here we give examples to define what a class imbalanced dataset means and why it should be handled differently.

2. Ways to overcome it -
   We go in detail about 3 ways to tackle the class imbalance problem.
   a.Sampling
   b.Setting Hyperparameters to assign weights
   c.Libraries like imblearn

3. Evaluation Methods
   We discuss the evaluation methods that best help us judge how our model is performing on an imbalanced dataset.

4. Custom loss
   We discuss a custom loss function that can considerably better our deep learning model and also explain why it does so.

5. Misc
   We go over some miscellaneous tricks and steps we can take to avoid common pitfalls.
   a.Train - Validation Splits
   b.Remove classes

Additional notes

My name is Aditya Lahiri and I am currently a Machine Learning intern at American Express, Big Data Labs. I am a Computer Science undergraduate from BITS Pilani, Goa and will graduate in December 2019. I love solving problems through data and code. Besides that, I enjoy attending meetups, talks and try my best to contribute to them. I have previously given talks in my college at events like Google Developers Group, Goa.

Here are the slides of this proposal-
https://docs.google.com/presentation/d/1_hiJQsbXHhrzlXxCtPUSpt9-FvMWNlNw1m6cBVPyGCE/edit?usp=sharing

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Title

Visualization for Data Scientists

Description

Currently, there are many scattered resources and libraries for data visualization with varying difficulty. This talk focuses on creating graphs from basic to advance level and comparing libraries for the same.

Duration

• 30 min
• 45 min

Audience

• Basic python knowledge required
• Beginner friendly talk

Outline

• Current visualization landscape
• Visualization examples using Jupyter Notebook
• Interactive visualizations
• Intro to plotly
• Creating dashboards using Plotly Dash

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Title

Spatial thinking and location intelligence

Description

Data can take many forms, It could be a text an image or maybe it is a bunch of coordinates. Though computer vision and natural language processing have hit it off spatial data science doesn’t get the attention it deserves. Spatial data has both social and industrial impact. Spatial data is useful in agriculture and for observing weather patterns to predict natural disasters. It is also very important for industries that deal with logistics and supply chain management. So in this talk I would like to focus on spatial data and how effective use of location intelligence can add immense value

Duration

• 30 min
• 45 min

Audience

This is a beginner friendly talk. Basic Python knowledge would be more than necessary

Outline

• What is spatial thinking and the state of location intelligence
• The need for spatial analytics
• Spatial support from databases and packages. Why Osgeo is awesome
• Problems that can be solved and processes that can be optimized with spatial data
• Talking some cool spatial use-cases by Uber, Airbnb, Walmart etc

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Title

Stream Processing Fundamentals with Apache Beam

Description

Introduction to the Beam model and using Apache Beam to understand the fundamentals of writing streaming data processing pipelines.
https://beam.apache.org/

Duration

• 30 min
• 45 min

Audience

Intermediate
Prerequisites: Basics of Python

Outline

• Introduction
• Apache Beam Model
  • Unbounded and Bounded Data
  • Event time - Processing time Skew
  • Windowing
  • Watermarks
  • Triggers
  • Accumulation Mode
  • What/When/Where/How
• Data Processing in Apache Beam
  • Core PTransforms
  • Examples
  • Beam execution model
• Applications / Use-cases
• Contributing
• More Resources

Additional notes

• https://www.linkedin.com/in/ttanay/
• https://github.com/ttanay

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Title

Machine Learning Bias

Description

Humans are filled with unconscious biases and when these are fed into Machine to Learn in the form of Data, the resulting AI model wouldn't be fair enough without Biases. This talk tries to introduce you to the world of Machine Learning Bias.

Duration

• 30 min
• 45 min

Audience

Those are interested Machine Learning and stuff around it

Outline

https://speakerdeck.com/amrrs/machine-learning-bias

Additional notes

https://speakerdeck.com/amrrs/machine-learning-bias

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Title

Title of the proposal, no buzz words!

Realtime streaming @ Grofers

Description

Describe your talk in simple sentences. Keep it short. (250 words)

Why realtime? How we are building?

Duration

• 30 min
• 45 min

Audience

Anyone

Outline

Most of the companies in the world right now moving towards realtime data streaming. How it is helping them. Why it is required?. How we are planning to build?. What are the different kind of approaches available. Technologies used for it.

Additional notes

I am an engineer.

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Title

Python: tooling, Code profiling and Security

Description

This talk will discuss how to write clean code in python using tooling ecosystem and doing sanity checks for security. (250 words)

Duration

• 30 min
• 45 min

Audience

Prerequisites: Python Know how. Additionally, talk content covers a beginner, intermediate and advanced audience.

Outline

Python tooling ecosystem
Doing Code profiling
Building security inside the code

Additional notes

You personal details, links to previous talks, etc.
https://twitter.com/aruns89
https://linkedin.com/in/arunsingh23

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Title

Introduction to Tweets Analysis in R

Description

Basic introduction of how text analytics could be performed on Tweets. This talk takes audience through a project of analysis tweets about Hasan Minhaj's Patriot Act.

Duration

• 30 min
• 45 min

Audience

Good to have Basic knowledge of R and Text / Data Analytics (not mandatory though)

Outline

• Text Analytics
• Twitter Data Format
• Text Analytics + Tweets
• Presentation

Additional notes

https://github.com/amrrs/hasan_india_tweets_analysis

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Title

Jenkins Pipeline

Description

Jenkins is one of the most successful open source projects used by Enterprises. With DevOps league, Jenkins has upscaled their game to provide Pipeline as a Code where the whole workflow of the build process is controlled via Code.
In this talk, we shall understand what is Jenkins Pipeline and how enterprises are using Jenkins Pipeline to adopt the DevOps culture.

Duration

• [] 30 min
• 45 min

Audience

This talk is for a beginner who wants to know what is Jenkins Pipeline.

Outline

Agenda:

• A real life analogy of Continuous Integration and Continuous Deployment.
• What is Jenkins Pipeline?
• How are Pipelines different from a normal Jenkins Job.
• Multi branch Pipeline
• How enterprises use Jenkins Pipeline to achieve End to End automation.
  If time permits, I will show a live demo in onboarding a Spring Boot Application to Jenkins Pipeline.

Additional notes

I'm Ajay. I'm a Polyglot Programmer, Solutions Architect at JP Morgan Chase - Profile.
As a hobby, I have been creating educational videos on new Technologies in the Youtube Channel - TechPrimers for the last 3 years.

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Title

R in the Real World

Description

This talk contains two sections predominantly - 1st explaining what's all (non-obvious) that are possible with R and 2nd, How well-known organizations are using R in their company.

• R is one of the most popular programming languages preferred in Data Science / Analytics.

Duration

• 30 min
• 45 min

Audience

This is a not-so-technical talk so doesn't matter much of audience technical expertise. Nevertheless, Can be more useful for people who are part of Data Science team or trying to get into.

Outline

https://github.com/amrrs/RinTheRealWorld/blob/master/slides_top_view.png

Additional notes

https://github.com/amrrs/RinTheRealWorld

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Title

Making Work Manager work for you

Description

Work Manager recently hit stable release in March and it's a good time to talk about why work manager is the best scheduling API available to android developers right now.

The talk would begin by bringing up all the existing scheduling APIs one by one and shooting them down and bringing up work manager at the end.

The second part would involve developing a basic app with work manager.

The last part would involve an API walkthrough and some nitty-gritties of work manager.

So this would be structured as a 3 part talk.

Duration

• 30 min
• 45 min

Audience

Intermediate

Outline

A detail flow/outline can be found on this article: https://ayusch.com/work-manager-in-android/
Talk would proceed along the lines of the article.

Additional notes

None.

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