What's new in Machine Learning?.

Motivation

I recently attended Google's I/O event and tuned in to the Machine Learning Keynote. I thought this blog would fit the timing as well

5 years ago tensorflow was open sourced by google and it has grown tremendously in production environments. Here are some of the recent advancements in Tensorflow and the Machine Learning/AI field.

Tensorflow Hub

Thousands of pretrained Machine Learning models to be open sourced and used by the community. Run Models in the browser or on the cloud and upload images directly on the site to test the model.

Vertex AI

A managed ML platform to deploy an AI in a production environment. Improving MLOps end to end. Speeding up development, training, and deploying along with continuous monitoring and training in production environments.

Visit the Official site https://cloud.google.com/vertex-ai

KnowYourData

Know your data is designed to help researchers and engineers understand datasets and improve data quality. It contains 70+ large ML datasets to use along with real-time filtering and grouping data. Easily compare what makes a good dataset as well as a bad dataset by finding bias and correlation.

Visit the Official site https://knowyourdata.withgoogle.com/

Tensorflow Cloud

Works as a pip package to easily run your models in the cloud. Just add tfc.run() in your model and it will run. This can be useful when working with large datasets where you can specify the GPUs and computing power you want in the code.

Visit the Official site https://www.tensorflow.org/cloud

ML Kit

Launching 4 new Vision APIs for a total of 12 APIs to supply developers with easy to use APIs such as face detection, language identification, image labeling, text recognition, and more.

Visit the Official site https://developers.google.com/ml-kit

Attending Google I/O was a unique experience in which I was able to learn new skills, meet new people and learn where to continue my learning. I look forward to attending other Developer Events and continue learning.