In the previous posts of the TFLite series, we introduced TFLite and the process of creating a model. In this post, we will take a deeper dive into Model Optimization. We will explore the different ...
TensorFlow Lite Model Maker: Create Models for On-Device Machine Learning
In this blog post, we will learn to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the custom dataset and ...
TensorFlow Lite: Model Optimization for
On-Device Machine Learning
The recent trend in the development of larger and larger Deep Learning models for a slight increase in accuracy raises the concern about their computational efficiency and wide scaled usability. We ...
Model Selection and Benchmarking with Modelplace.AI
In this post, we will learn how to select the right model using Modelplace.AI. Selecting the right model will make your application faster, help you scale it to millions of requests, and save a ton ...
MRNet – The Multi-Task Approach
Our last post on the MRNet challenge presented a simple way to approach it. There you learned to make a separate model for each disease. And ended up with three models. Time to up your game! Now ...
Generative and Discriminative Models
Most of the Machine Learning and Deep Learning problems that you solve are conceptualized from the Generative and Discriminative Models. In Machine Learning, one can clearly distinguish between the ...
