Description
Deployment of Machine Learning Models in Production Python is a machine learning model deployment training course using BERT, DistilBERT, FastText NLP models along with Flask, uWSGI, and NGINX at AWS EC2. BERT is a pre-trained language representation method, which means that we train a general language understanding model on a large collection of texts (such as Wikipedia) and finally train it for natural language processing tasks (such as question specific answers). ) We use. BERT is far more powerful than its previous competing methods because it is unsupervised and has a deep two-way system for pre-trained natural language processing.
What in the course of Deployment of Machine Learning Models in Production Python you will learn:
- Completing natural language processing programs
- How to work with BERT in Google Colab
- How to use BERT for text classification
- Expanding ready-made machine learning models
- Refine and extend machine learning models using Flask
- Application of machine learning models in Ubuntu and Windows Server, AWS
- Understand the difference between DistilBERT and BERT
- Optimizing your natural language processing codes
- How to develop and deploy FastText models on AWS
- Learning Multi-Label and Multi-Class Classifications in Natural Language Processing
Course details
Publisher: Udemy
Instructors: Laxmi Kant
English language
Training level: introductory to advanced
Number of courses: 85
Duration: 9 hours and 39 minutes
Course topics:
Course prerequisites:
Introductory knowledge of NLP
Comfortable in Python, Keras, and TensorFlow 2
Basic Elementary Mathematics
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
Password file(s): www.downloadly.ir
Size
3.8 GB