AutoML + Cloud: The future of machine learning

Our discussion will focus on why modern applications require AutoML over traditional machine learning. From development to deployment, it helps organisations deploy AIML models into real life. The impact it will have on AIML. In addition to exploring the various AutoML services provided by Google Cloud, the talk will be hands-on about building and deploying the model.

Session Duration: 45 mins

Agenda for the Session:
a. What is Automated Machine Learning (AutoML)
b. Why Machine Learning on Cloud
c. Advantages of AutoML with respect to why companies are shifting towards AutoML
d. Working of AutoML Vision
e. Let's Build AutoML Vision Model on GCP
f. Quiz

AI powered databases : Mindsdb

In this session we will be taking about mindsdb and a live demonstration of how it works. Exploring how AI tables are transforming the world of AI data. The dynamic databases are supported by AI tables and allow Oraganisation to directly analyse data inside the database and engineer solutions.we will be doing a hands on session on Time series data and Forecasting data elements. How AI can empower databases. We will decode the technology behind this.

How MindsDB is Impacting the Machine Learning World

Mindsdb is an open-source AutoML startup which aims to solve ML modelling & deploying problems with the help of AI in databases. With the help of MindsDB, you can build, train, optimize, and deploy your ML models without the need for other platforms. Predictive Points and Analytics can be fetched with the use of simple queries on the data and ML models 📙. With MindsDB, you can identify patterns, predict trends, and train models using AI and machine learning in databases. Incorporating machine learning into a database speeds up the development of ML.

Session Length: 50 minutes
Mode: Online (LiveStream Youtube)
Youtube: https://www.youtube.com/watch?v=YngjfwJLplA&t=1501s

Limitation of the Large Language Models (LLMs)

In this talk, we will explore some of the key limitations of LLMs.

Large language models (LLMs) have revolutionized the field of natural language processing, but they are not without their limitations.

Agenda of the Talk -

- Limitation of LLMs -
Hallucinations
Optimization of Context Length
Speed and Cost
Biasedness
Incorporation of Multimodality
LLMs for Other Languages
Ethical Data Generation
Data Privacy
Prompt Injection
- Q&A

Duration - 20 mins

The talk will also discuss the need for retrieval-augmented generation (RAGs) to address some of the limitations of LLMs. RAGs are a type of LLM that are trained to retrieve and synthesize information from a large corpus of text.

The talk will conclude by discussing the future of LLMs and RAGs, and the potential for these technologies to revolutionize the way we interact with system.

Unlock the Data - EDA & AutoEDA

The seasons delves in understanding the process of EDA and also focusing the importance. Also, Hands-on with AutoEDA.

Agenda for Session -

Introduction to Exploratory Data Analysis
Why there is a need of EDA
Importance of EDA in Data Science and ML
Steps involved in EDA
Exploring Data Distributions and Patterns
Handing missing data and outliers
Visualization Techniques for EDA
What is Automated EDA
Techniques for Automated EDA
Various Tools for Automated EDA
Hands on with EDA and AutoEDA (Spaceship Titanic)
Q&A

Duration - 90 mins

World of AutoML on GCP

The session focuses on understanding the AutoML in the GCP and also building the AutoML Vision Model for the classification of the various car damage.

Agenda of the Session -

1. Basics of Cloud Machine Learning
2. Machine Learning Refresher
3. Types of GCP Machine Learning
4. GCP ML Clients
5. Machine Learning API Services
6. Dive into the AutoML
7. Building AutoML Vision Model on GCP
8. Q&A

Session Length: 120 minutes
Mode: Online (LiveStream Youtube)
Youtube: https://www.youtube.com/watch?v=xr5bHV2syhk