Udemy – Deploy machine learning models in production

explanation

Deploy machine learning models in production | Python is a machine learning model course that uses BERT, DistilBERT, and FastText NLP models with Flask, uWSGI, and NGINX on AWS EC2. BERT is a pre-trained language representation method. This means teaching a general language understanding model on large text collections (e.g. Wikipedia) and eventually using it for natural language processing tasks (e.g. specific answer questions). ) we use. BERT is much more powerful than previous methods because it is unsupervised and has a deep, interactive system for processing pre-trained natural language.

Ins and Outs of Deploying Machine Learning Models in Production | You will learn Python:

A complete natural language processing program
How to use BERT with Google Colab
How to classify text using BERT
Extend a ready-made machine learning model
Improve and scale machine learning models using Flask
Using machine learning models on Ubuntu and Windows Server, AWS
Understanding the Differences Between DistilBERT and BERT
Natural language processing code optimization
How to Develop and Use FastText Models on AWS
Learn about multi-label and multi-class classification in natural language processing