We would like to announce the results for Call For Proposals(CFP) for PyData Delhi 2018.

The following topics are accepted:

Talks

  1. Convolutional Neural Nets for Language Modelling - Anuj Gupta (Former Director, ML @ Huawei Technologies)
  2. Social Bias in Machine Learning, Ethics, and the need for Interpretation - Janu Verma (Data Scientist @ Hike Messenger)
  3. Building an Intent Classification Model from Scratch using Keras - Yada Pruksachatkun (Capital One Fellow @ New York University Center for Data Science)
  4. Practical Object Detection and Classification - Jaidev Deshpande (Practice Lead - Data Science @ Juxt Smart Mandate)
  5. Creating art with neural networks - Srishti (Machine Learning Engineer @ Hike Messenger)
  6. Exploratory Data Analysis and Techniques for optimum feature selection in R - Yash Kumar Singhal (Undergraduate Student @ JIIT, Noida)
  7. Fooling and protecting Deep learning models - Divyam Madaan (Deep Learning Researcher @ for.ai)
  8. Mapping Disasters in South - East Asia using Twitter - Devanshi Verma (Undergraduate Student @ NSIT)
  9. Applying Machine Learning and Deep Learning to Geospatial Data - Rohit Singh (Director, Deep Learning Dev Labs @ Geonuma Software Pvt Ltd), Co-presented by Divyansh Jha
  10. Introduction to Quantum Computing - Nilay Shrivastava (Undergraduate Student @ NSIT)
  11. Speech Synthesis engine for generating human level natural voice - Rishikesh (Data Scientist at Humonics Global)
  12. Suicidal Ideation Detection - Ramit Sawhney (Undergraduate Student @ NSIT)
  13. Dash : Building beautiful interactive web visualization apps natively in Python - Madhur Tandon
  14. From “Hello World” to production, building and running Machine Learning models into production - Bhanu Sharma (Machine Learning Engineer @ SpotDraft)
  15. DIY guide to convert Speech-to-text with DeepSpeech AND Text-to-speech with WaveNet - Kajal Puri (Data Scientist @ Fractal Analytics)
  16. Image Classification using Deep Learning in Python (Capsule Networks) - Sandeep Saurabh (Senior Data Scientist @ BRIDGEi2i Analytics Solutions)
  17. Probabilistic Programming: An introduction - Mayank Satnalika (Undergraduate Student @ VIT)
  18. Auto Encoder & Clustering based Data Encryption restoring Patterns. - Yatin Bhatia, Co-presented by Anamika Kumari and Ankit Rathi
  19. Kubeflow: scalable and portable machine learning using Jupyterhub and Kubernetes - Akash Tandon (Member, Data Engineering Team @ SocialCops)

Workshops

  1. Introductory workshop on Computational Machine Learning using Julia - Abhijith Chandraprabhu (Data Scientist @ Julia Computing)
  2. Network Science, Game of Thrones and US Airports - Mridul Seth (Student, Université Catholique de Louvain)
  3. Practical Pandas - Nikhil Singh (Undergraduate Student @ DTU)
  4. Awesome Data Analytics using Elastic Stack - Aravind Putrevu (Developer Advocate @ Elastic)

Above CFP submitters will also receive email notification today.