Top 9 Python Libraries for Machine Learning in 2022
From data visualisation to deep learning libraries, Python is the most valuable language for machine learning.
A deep dive into image data preprocessing by TensorFlow
Preprocessing prevents from overfitting
Building a question-answering model with FNet Encoder
The FNet Encoder is based on the Fourier transform
Speed-up hyperparameter tuning in deep learning with Keras hyperband tuner
Hyperband is a framework for tuning hyperparameters
How to deploy and monitor your Keras model with Comet?
A detailed implementation of usage of Comet platform for deploying and monitoring a model.
Methods to Serialize and Deserialize Scikit Learn and Tensorflow models for production
This article briefs about the various methods to serialize and deserialize Scikit Learn and Tensorflow models for production
Keras turns seven: A look back
The primary author and maintainer of Keras is Google engineer François Chollet.
TensorFlow Recommenders vs Pytorch TorchRec: A comparative analysis
TFRS is built on top of Tensorflow 2 and Keras.
How to use Torchbearer for fitting ML models with PyTorch?
Torchbearer is python based library which is basically a model fitting library for PyTorch models and offers a high-level metric and callback API that can be used in a variety of applications.
A guide to TensorLayer for efficient deep learning development
In this post, we’ll look at TensorLayer, a Python-based machine learning tool.
How to Visualize and Debug Machine Learning Models using ELI5?
From this post you will come to know how particular predictions are being made and how models focus on various aspects of parameters it has learned.
DeepSpeed Vs Horovod: A Comparative Analysis
A comparative analysis of open-source deep learning optimization libraries DeepSpeed and Horovod for advancing large-scale model training.
