Description
Deployment of Machine Learning Models in Production | Python is a machine learning model diploma training course using BERT, DistilBERT, FastText NLP models along with Flask, uWSGI, and NGINX at AWS EC2. BERT is a pre-taught language presentation method, which means that we teach a general language comprehension model on a large collection of texts (such as Wikipedia) and eventually use it for natural language processing tasks (such as specific answer questions). ) We use. BERT is far more powerful than its predecessor methods, as it is unsupervised and has a deep two-way system for processing pre-trained natural language.
What in the Deployment of Machine Learning Models in Production | You will learn Python:
- Complete natural language processing programs
- How to work with BERT in Google Colab
- How to use BERT to categorize texts
- Expand ready machine learning models
- Refine and extend machine learning models using Flask
- Using machine learning models in Ubuntu and Windows Server, AWS
- Understand the difference between DistilBERT and BERT
- Optimize your natural language processing codes
- How to develop and use FastText models on AWS
- Learn Multi-Label and Multi-Class classifications in natural language processing
Course specifications
Publisher: Udemy
Instructors: Laxmi Kant
Language: English
Education Level: Introductory to Advanced
Number of Courses: 85
Duration: 9 hours and 39 minutes
Course topics:
Prerequisites course:
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3.8 GB