Introduction

I recently had the opportunity to attend a special event, and I wanted to share my experience with you. From the excitement leading up to the event to the unforgettable moments during the event, it was a day I will never forget

As the Event was scheduled for the 10th of Dec 2022 at venue Google RMZ infinity ✨

Topic and Session Conducted

Introduction about Jax

The session was very informative and an introduction to the new Open Source Lightweight machine learning library JAX

I have learned about JAX - A Machine Learning Framework for transforming numerical functions from Rengaraju

Google JAX is a machine learning framework for transforming numerical functions. It is described as bringing together a modified version of autographed and TensorFlow's XLA.

The JAX is very simple and blazing fast to execute 🔥. It has been written in python and C++ which makes it easy to learn and implement on various platforms. It can overcome the existing library like NumPy and be a lightweight extension of the TensorFlow library.

Hence JAX is very promising and it will be having good future for machine learning. I hope one day I can implement or use it as one of my projects 😁

MLOps in the Google Cloud Platform

The MLOps is rapidly increasing nowadays and during the session, I learned that there is a market gap for a good MLOps engineer. Many organization are been searching for them. The session is been taken by Joinal Ahmed

Here is an image to get a clear idea about MLOps. It's quite similar to the DevOps MLOps and almost follows the same practice and culture. They work closely with DevOps folks and many of the DevOps are been switching to MLOps.

Joinal Ahmed has introduced How MLOps can be implemented at the Google Cloud Platform

Some key take points

• Vertex AI is basically market place for pre-trained models

• Jupyter Notebook helps to import existing books and work everything on the cloud

• Data Pipeline and Cleaning help to implement and train the model with a good accuracy score

• Data Set can be uploaded or imported to the Google Cloud Platform for better management to train model

• ML Models are placed in training and testing of the model are been done in a closed playground before deploying the app in a real-world case scenario

Networking:

I have talked with a lot of experienced people working in the industry and gained insights into what are they expected from fresher and new graduate people. It was a great experience to connect with them.

Here are some of the pictures from the event 📸

Conclusion

I came to know and feel the vibe of the ecosystem on the Google Office at such an early age before going to the co-operate world and also realized how hard even I have to work for my dreams to achieve them.

P.S. I have been uploading these blogs lately just finished my exam and just with all the exams, practicals, and submissions. I will be continuing my journey of learning in public and many blogs are been soon coming up. Please Stay Tuned for it 😄