Welcome to PyCon India 2023 CFP
- Join us for PyCon India 2023, the 14th edition of the premier Python conference in India, taking place in the vibrant city of Hyderabad from September 29 to October 2.
- This annual gathering brings together Python enthusiasts, developers, and industry professionals for four days of inspiring Talks, hands-on Workshops, and networking opportunities. Visit the official website for more information: https://in.pycon.org/2023/
Talks
- Talks should be 30 minutes long (including Q&A – 5 mins) and can be on any topic related to Python.
Schedule
- Talks will be there across the morning and evening sessions on September 30, 2023, and October 1, 2023,.
- We may have up to 3 parallel tracks of talks in each session. The morning session will run from 10:00 AM to 1:00 PM. The evening session will run from 2:00 PM to 6:00 PM.
Format
- The format of each talk will be up to the speaker but should include a mix of lectures, demos, and Q&A.
Workshops
Workshops are 3 hrs long interactive sessions where attendees can learn by doing.
Schedule
- Workshops will be held on September 29, 2023, across two morning and evening sessions.
- We may have up to 3 parallel tracks of workshops in each session. The morning session will run from 10:00 AM to 1:00 PM. The evening session will run from 2:00 PM to 5:00 PM.
Format
- Workshops are aimed at beginner, intermediate, and advanced experience-level participants.
- Workshop proposals must include a detailed outline of the covered topics and allocated time.
Important Dates
- CFP for Talks and Workshop closes on August 5.
- Selected Talks and Workshops will be announced on September 4.
What to Propose
Any topics of interest to Python programmers, with a focus on the following:
Lessons learned from using Python in projects, including unconventional and conventional wisdom and advice for similar problem-solving. E.g., I tried Python for video processing or in my medical imaging project, and here are the lessons.
Contributions to improving the Python language/ecosystem, such as creating libraries or proposing optimizations.
Knowledge gained from other languages, like type systems, functional programming patterns, or logic programming.
Thoughts on tech culture, diversity and inclusiveness, the physical and mental health of programmers, productivity improvement, workplace issues, and their impact when using Python.
Alternatively, consider offering teaching sessions on niche topics, recent technologies, or scientific papers, even at a beginner level.
Rehearsals
Shortlisted speakers will be expected to participate in rehearsal sessions. We will conduct Rehearsals via teleconferencing, where the speaker shall give a mock run of their talks in a time-bound manner.
The audience will include volunteers, reviewers, and possibly other speakers. We will give feedback to speakers if necessary.
This exercise aims to ensure speakers are ready with their talks beforehand. And also to ensure they can finish the talk within the stipulated time. It is also helpful for the speakers to get feedback on the content delivery and presentation.
Participation in the rehearsal sessions is likely to be required - chances of an unrehearsed talk making it to the final stage are substantially lower.
Diversity
We in the Python community believe in making our community more diverse. This suggests that we encourage content from diverse walks of life and also want to improve participation from under-represented groups.
Our goal is to maximize content from under-represented groups. You can help us by encouraging your friends, family, and colleagues to submit talks. You can also help by mentoring.
Also, note that we have a strict code of conduct. In intent and practice, we are committed to making the conference a pleasant, welcoming, and harassment-free experience for everyone, especially for under-represented groups.
Speaker Best Practices
We've compiled a set of detailed best practices - take a look.
Questions?
Ping us on Zulip. In addition to it, you can reach out to CFP volunteers:
- Soumendra Kumar Sahoo, CFP Lead – DM on Zulip
- Dr. Murali, CFP shadow lead - DM on Zulip
Proposal Sections
- Developer tools and automation - Tools and practices for automating development workflows and enhancing productivity like DevOps, Testing, CI/CD, Containers, Orchestration, Logging, and Monitoring, Selenium
- Concurrency - Approaches to concurrent Python programming using multiple threads like Multiprocessing, Multithreading, Async
- Core Python - Focused on understanding and mastering fundamental Python concepts and syntax like Documentation, Python Libraries, Language Features & Internals, Python Implementations
- Culture and Society - Exploring cultural aspects and societal influences like Diversity, health, life, education, productivity, workspace issues, community, coding for causes
- Ethics and Philosophy - Examination of ethical considerations and philosophical questions in technology like Govt. Policies, Responsible AI, Privacy and Bias.
- Others - Other topics not explicitly covered in the above sections like Quantum Computing, Storage, etc.
- Cloud Computing - Using Python to leverage cloud-based services and infrastructure like Cloud services (AWS, GCP, Azure, etc.) for Python, IaaS for Python.
- Blockchain - Understanding and developing blockchain systems and Web3.0 using Python.
- Distributed Computing - Techniques for processing data across multiple machines or processes using Python like PySpark, Dask, Distributed ML (Horovod), MPI (Message Passing Interface).
- Embedded Python and IOT - Using Python in embedded systems and Internet of Things (IoT) devices like MicroPython, Python on Hardware, Robotics, Arduino, and Raspberry Pi.
- Desktop Applications - Design and implementation of applications for desktop environments using Python like Qt, GTK+, Tkinter, Gnome, KDE.
- Web & App development - Building interactive websites and mobile applications using Python like APIs, REST, GraphQL, PyScript, Django, Flask, FastAPI, Kivy.
- Networking and Security - Concepts and practices for secure, efficient networking using Python like Network Programming, Network Security and Encryption.
- Game Design and 3D Modelling - Creation and manipulation of 3D models, AR/VR and principles of game design using Python.
- Scientific Computing - Using Python to solve complex scientific and mathematical problems like Python usage in scientific computing and research. GIS, Mathematics, Simulations.
- Data Science, AI & ML - Exploration and implementation of data science techniques, artificial intelligence, and machine learning algorithms using Python like Generative AI, Data Analytics & Visualisation, Data Engineering, Speech Processing, NLP, Computer Vision, MLOps and Others.
Proposal Types
- Workshops - Workshop is a 3 hr interactive session where attendees can learn by doing. Workshops can have one or more facilitators.
- Talks - Talk is a 30 minute presentation on a specific topic related to Python.
Selected Proposals
Workshops
2 3
1. Mastering Retrieval Augmented Generation (RAG) with LlamaIndex and LLMs
0 3
2. All Them Data Engines: Pandas, Spark, Dask, Polars and more - Data Munging with Python circa 2023.
0 4
3. Instruction Finetuning: Unlock the Power of Large Language Models
Talks
0 6
1. Taking a Multilingual Conversational Engine to Production: Theory to Reality
0 9
2. OpenAI Whisper and it’s amazing power to do fine-tuning demonstrated on my mother-tongue
0 0
3. Fine-Tuning Insights: Lessons from Experimenting with a Large Language Model on Slack Data
0 0
4. PyVelox: Interfacing Python bindings for the unified execution engine by Meta
0 1
5. Evaluating Generative Vision Models: Insights into the Fréchet Inception Distance and CLIP
0 3
7. Revealing Uncommon Tricks: 25 Obscure Pandas & NumPy Hacks learnt over 5 years of being a Data Scientist
1 9
8. Data Pipelines in Production - Bad vs Best Practices
0 0
9. The Why Conundrum - Practical causal inference and discovery with python
Data Science, AI & ML
2 1
1. AutoGPT: The AI That Will Make You More Productive
0 0
2. Python for MLOps: Simplifying and Scaling Machine Learning Operations
2 3
3. Mastering Conversational AI with RASA: A Transformative Hands-on Workshop
2 4
4. LLM Building on our own data | Low Internet Availability Space | PDF - Video Summarisation using OpenAI
0 2
6. Dive deep into Video Surveillance to redefine women's safety in the Indian roads
0 4
7. Learn and Adapt: Shaping AI with Reinforcement Learning using the Gymnasium Framework
2 15
8. Algorithmic Trading Unveiled: From Complexity to Profits with AI Integration
0 1
10. Demystifying MLOps: Managing the Machine Learning Model Deployment Process
0 4
11. Model deployment with Nvidia Triton and deploying LLMs
1 6
13. LLMs for the Masses: How to Train Your Own Language Models on a Limited Budget
0 22
14. From Chaos to Order: How MLFlow Transforms Experiment Tracking and Reproducibility
2 1
15. The Sound of Your Footsteps can Predict for Dementia
0 1
16. Unleashing the Power of Computer Vision to detect Animal Behaviour and insight generation using Python
0 2
18. Demystifying Explainable AI: A Comprehensive Guide with Python
0 6
19. Mathematical Modelling of AI: Unveiling Insights Beyond Artificial Intelligence
0 45
21. Virtual Assistants 2.0: How Gen AI elevates the game of domain-specific virtual assistants
0 3
22. ChatGPT and Elasticsearch: OpenAI meets private data
0 4
23. Framework-agnostic Generative AI with New Keras Ecosystem
0 1
24. Building LLM powered applications using langchain
0 4
26. Datafication of Indian Court Judgments using Natural Language Processing (NLP)
0 0
27. Voxel (3D) object detection/segmentation from scratch
0 0
28. ML Defender: Deep Learning Based Image-Malware Detection
0 3
29. Building Your Semantic Search Engine Using Vector Databases and Langchain
1 22
31. Python-based approach to simplify complex JSON structures by flattening them
0 7
32. Proactive System Failure Detection with Log Analysis
1 0
34. Explainable AI: Demystifying Complex Models with Shapley Values
0 0
35. Satellite Image Processing and Analysis using Python
0 0
36. Integer Optimization in Python: A Practical Exploration through case studies and Beyond
0 0
37. Wayfarer AI: How I Built a Web-Searching and Multimodal Travel Chatbot with LLMs, Powered by Langchain & Gradio
0 0
40. Accelerate Your Data Science and MLOps Workflow with DVC, PyCaret, and FastAPI
0 1
41. Exploring the Enigma of Diffusion models: Revealing the Science Behind Artificial Creativity
0 0
43. Data Engineering and Machine Learning using Snowpark - Snowflake's Developer Framework
0 0
44. Streamlit to Build & Deploy Apps like a Data Scientist
0 0
45. Exploring CoNLL-U Annotation Schema for Linguistic Structures with Python
0 0
46. ⚡Streamlining Machine Learning Projects: An Introduction to the Python Machine Learning Template
0 5
48. Data driven decision making using Structural Equation Modeling (SEM)
0 0
49. How YouTube is Democratizing Data Science Education?
0 0
51. Build production ready LLM powered applications using Langchain and FastAPI
0 2
53. Beyond the Hype: Understanding Diffusion Models for Cutting-Edge Generative Artistry
0 3
54. Build a production-ready database, search engine, and integrate semantic search with OpenAI using PyMongo
0 1
55. Build semantic search with MongoDB Atlas, OpenAI and PyMongo
0 1
56. The Rise of the AI-Powered Developer: Are Humans Still Relevant?
0 1
57. Creating data-aware applications with large language models
0 0
58. On-premise solution to unleash the power of large language models (LLMs)
0 0
59. Explainability approaches for deep learning, shining light on black box AI models
0 2
62. Transforming Audio-Video Content Management: Unleashing the Power of OpenAI Whisper and GPT at Egnyte
0 1
63. Pandas vs Polars: The Evolution of Data Manipulation in Python
0 3
64. BackdropAI: AI-powered context-based background changes for immersive live streaming
0 0
65. Doppelgänger: A tool to cater the need of data governance for businesses.
0 1
66. Building Sustainable Applications with Python: Navigating Generative AI, Computer Vision, and More with RecyloVision
0 24
67. Ingest, Analyze, Validate, Train, Test, Deploy: TFX - One Tool to Rule Them All
0 1
68. Build complex chat apps using LLMs with ChainFury
0 0
69. Interpreting rationale behind Machine Learning model predictions using InterpretML
0 1
71. The Quest for Knowledge: Enabling Intelligent Chats and Fast Document Retrieval through Semantic Search and LLM with Langchain
0 2
72. Building a Production Ready LLM Application using MongoDB Atlas
0 0