Index

1. ​Effective Communication between Scientists and Non-scientists
2. ​​Data Labeling and Relabeling in Data Science                                                      
3. Understanding and Measuring Data Quality
4. The Metric Layer and how it fits into the Modern Data Stack
5. Team Development Tips for Engineering and Product Leaders
6. Five 5-minute Team-Building Activities for Remote Teams
7. ​​Benefits of FAANG companies for Data Science & ML roles
8. Why Data Democratization is important to your business?
9. When is the right time to migrate to Kubernetes?
10. How to ensure Data Quality through Governance
11. Data Labeling: The Unsung Hero Combating Data Drift
12. ML Engineer vs Data Scientist
13. Knowledge Distillation: Principles, Algorithms & Applications                
14. Best Practices for Improving Machine Learning Models                           
15. Developing AI/ML Projects for Business - Best Practices                        
16. How to build AI Teams that Deliver?                                                                  
17. Why Corporate AI Projects Fail? Part 1/4                                        
18. Why Corporate AI Projects Fail? Part 2/4                                       
19. TLDR: AI for Text Summarization & Generation of TLDRs   
20. Covid or just a Cough? AI for Detecting Covid-19 from Cough Sounds 
21. Reskilling India for an AI-First Economy                                                     
22. Fact-checking Covid-19 Fake News                                            
23. AI-enabled Conversations with Analytics Tables