Machine Learning

Synopsis: 

• Metrics: AUC, ROC, f1score, Recall and Precision 
• Machine learning algorithms 
• Working with Scikit-learn 
• Training, Test, Validation set 

Resources: 

• https://developers.google.com/machine-learning/crash-course 
• Machine learning  
• Overview of the different approaches to putting Machine Learning (ML) models in production
• Applying Natural Language Processing to Healthcare Text at Scale
• Basics Of MLOps: ML + Dev + Ops
• Fighting Misinformation in News using NLP
• Topic Modeling for Human

Algorithm

• TopicBERT: A cognitive approach for topic detection from multimodal post stream using BERT and memory–graph

NLP

• Cleaning & Preprocessing Text Data by Building NLP Pipeline
• Continuous NLP Pipelines with Python, Java, and Apache Kafka
• https://paperswithcode.com/dataset/snli
• https://paperswithcode.com/dataset/scirex
• News classification with Transformers

MLFlow

• ML-IN-PRODUCTION-MADRID – Practical Workshop for Spain High Speed Train