PyCon India - Call For Proposals
The 10th edition of PyCon India, the annual Python programming conference for India, will take place at Hyderabad International Convention Centre, Hyderabad during October 5 - 9, 2018.
PyCon India invites all interested people to submit proposals for scheduled talks and tutorials. All topics of interest to the Python community will be considered. Standard presentation talk slots will be 30 minutes. Tutorial slots will be two and half hours long.
Schedule
- October 5: Tutorials
- October 6-7: Talks
- October 8-9: Dev Sprints
Who Should Submit a Proposal?
You. Your friends. Your friends' friends. Anyone with any level of Python knowledge is a candidate for a great topic at this conference. As we get attendees of all kinds, we need speakers of all kinds. In all ways and manners, we try to assemble the most diverse conference we can, and we do that with your help.
Whether you got started with Python last month or you've been around for 20 years, we think you've got something to share. The Python community is stronger than ever and we're still reaching new areas, new industries, and new users. Be a part of growing Python by helping us change the future.
In particular, we welcome submissions from people that have never done a talk before! And if you want help preparing a talk, let us know! Volunteers are eager to help new people with talks.
How to write a proposal
If you have an idea (or don’t!) and want to speak, here’s a very rough process of what you should do next:
- Brainstorm or mind map to expand upon your ideas or knowledge in search of a general topic
- Write a paragraph or two, or some bullet points, to outline the core concepts you want to communicate and what people might learn from your talk
- Get someone you trust to read your notes and tell you what they think they’d learn
- Ask one of our mentors for help with building up your submission
- Practice!
This public speaking repository, maintained by VM Brasseur, has many useful resources to help you polish your proposals and talks.
Code of Conduct
All speakers will be expected to have read and adhere to the conference Code of Conduct, listed below and also at our website. In particular for speakers: slide contents and spoken material should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate, and neither are language or imagery that denigrate or demean people based on race, gender, religion, sexual orientation, physical appearance, disability, or body size.
Mentors
Presenters, regardless of experience, sometimes want a little help. If you’d like any help in proposing, preparing, or presenting your talk, feel free to contact one of our mentors! A mentor is an experienced presenter who has volunteered to help other presenters.
If you are a first-time speaker, or looking for help to give a shape to the idea that you have in your mind, or just appreciate another set of eyes, our mentors are here to help. If you would like to be matched with a mentor to help with your proposal(s), request a mentor here.
Important Dates
- July 10: Proposal submission deadline
- July 29 : Workshop finalization and first round decision for talks
- August 12 - Final round decision for talks
- September 10 - Schedule announcement on the website
Have a question? Unsure about anything?
If you have questions about the CFP process, you can reach us any time at cfp@in.pycon.org
Proposal Sections
- Others - Everything else that may be of interest to the audience of PyCon India
- Web development - Web frameworks and RESTful APIs
- Networking and Security - Network Programming, Async, Network Security and Encryption
- Embedded python - MicroPython, Python on Hardware, Robotics, Arduino and Raspberry Pi
- Developer tools and Automation - Testing, CI/CD, Containers, Orchestration, Logging and Monitoring
- Data science - Data Analysis, Scientific Computing, Machine Learning and Data Visualization
- Core python and Standard library - Language Features, Python Implementations, Extending Python and Standard Library
Proposal Types
- Talks - Talks are focused on a topic for 30 mins
- Workshops - Workshops are in depth hands on session for 2 hours and 30 minutes
Selected Proposals
Talks
3 8
1. How Helpshift built machine learning platform using Python at large scale
2 13
2. Managing flood risk in this modern age - An Introduction to Geospatial Analytics with Python
0 1
3. Language Model (Text Analysis) using Python from scratch
3 6
4. Using NLP to demystify "Terms and Conditions" and summarize the contents
2 3
9. The art of effective visualization of multi-dimensional data - A hands-on approach
Workshops
1 13
3. Exploring PyTorch for AI assistance in Medical Imaging
Data science
5 16
1. Dask: Distributed Data Science in a pythonic way
2 38
2. Through Python to the Stars! - Orbital Mechanics Made Easy and Open-Source
3 146
3. From scratch to ML - The machine learning library you really understand and explaining its predictions with LIME.
2 1
6. Sequence Embeddings in Python: Classification & User journey Comparison
3 5
7. An intro to Web Scraping, dos & don'ts and the challenges in Scaling it to huge volumes
0 34
8. Swing and a Miss: Deploying machine learning models for IoT enabled devices using Python
0 24
9. Deep Learning using Python from Scratch - Image Classification
0 1
12. Mozilla's DeepSpeech and Common Voice projects
1 31
14. Convolution Neural Networks without any frameworks
0 2
16. Object tracking vs Object detection- a comparative analysis
4 17
21. Predicting Sunspots and Solar Flares with a tinge of Python
6 55
22. How ROBUST is Artificial Intelligence ? ~ AI using Python
1 11
24. Follow the Sequence in Deep way - Introducing Sequence Models
2 10
27. Cutting edge NLP classifiers in one hour with Python and fastText
1 3
32. Building A Lip Reading System To Recognise Visual Speech Using Python
0 21
34. Understanding and Implementing Recurrent Neural Networks using Python
0 18
36. Bag-of-Features: Representing Text & Image Data as Numerical Vectors
1 48
38. How to talk to your computer - A 101 on Natural Language Processing with Python
0 5
39. Power of Data and Working with it using Python
0 0
41. Learning to build Neural networks from scratch using tensorflow
0 57
44. Gospel of LSTM : How I wrote 5th Gospel of Bible using LSTMs
0 1
46. Deep Learning with Keras : Building an AI that Talks like Shakespeare or Trump
1 3
47. Fuzzy Matching - Smart Way of Finding Similar Names Using FuzzyWuzzy
1 1
48. Case Study in Travel Business - Understanding agent connections using NetworkX
2 4
49. Case Study in Travel Business - Time Series Analysis with Seasonal Data
1 2
52. Language Model (Text Analysis) using Python from scratch
0 47
53. Understanding State of the Art Facial Recognition
0 1
55. Bringing analytics in hands of leaders: Natural Language Query in Python
2 77
56. Building your own Emotion recognizer from Scratch !
0 3
57. Detecting offensive messages using Deep Learning: A micro-service based approach
0 1
58. Quick and easy implementation of Smile Detector on your Webcam using python and openCV from Scratch without any Neural Network and for beginners .
7 0
59. Google Stock Price Time Series Prediction with RNN(LSTM) using pytorch from Scratch
0 13
60. Processing Billions of Records Per day with Python
0 1
62. Demystifying speech recognition with Project DeepSpeech
2 65
63. The Advent of Deep Neural Networks. Neural Network implementation without ML libraries and extending them with Tensorflow.
0 16
66. Analyzing the impact of weather on human sentiments
2 4
67. Document Clustering with Word2vec and Hierarchial Clusters
3 44
68. Advanced ML: Learn how to Improve Accuracy by optimizing Hyper-Parameters using Hyperopt
1 15
69. How to implement a YOLO object detector from scratch using PyTorch and OpenCV
0 41
72. Understanding customers in better way- A Market research application using python
0 4
74. Comprehensive Study of Distance Metric Learning in Nearest Neighbor Algorithm
9 43
75. Synthesising Images from text using Generative Adversarial Networks
0 11
76. Deep Dive : machine learning and media -building your own recommendation system from scratch
5 5
77. Accelerating Transfer learning using Effective Caching and How to Debug TensorFlow programs
1 4
79. A Comprehensive Overview of dealing with Imbalanced Datasets in Python
0 4
81. Managing Tensorflow training and inference with a simple RESTful framework
1 2
82. Forecasting and observing Airfare trends using Python and Neural Networks
3 2
84. Something for Nothing: Boostrapping Text Classification
1 23
85. Named Entity Recognition in Python
0 0
86. Speech recognition using Python: how a computer can tell if you're angry
63 75
87. Decode human behavior through code: A counter-intuitive approach
4 2
88. Speech Synthesis engine for generating human like natural voice
1 0
89. Capsule Networks - overcoming limitations of Convolutional Neural Networks
1 22
92. Applying Deep Learning for NLP using Python - Workshop
1 5
93. Coding for everyone - Setting up coding workshops in challenging environments
1 3
96. Machine Learning as a Service: How to deploy ML Models as APIs without going nuts
2 7
103. Implementation of Linear Regression from scratch using numpy, pandas and matplotlib
0 28
104. Feature Engineering for Kaggle and Machine Learning Competitions
0 2
106. Harnessing Open Data to build user profiles using python sci-kit
1 50
109. Generative Modelling using Python : An introduction to GAN's and VAE's
1 4
110. Tricks and tips for using numpy and pandas(Some standard libraries)
1 7
111. Training and optimizing an Artificial Neural Network for classification from scratch with just numpy.
2 1
115. INTELLIGENT CATEGORIZATION OF PRODUCT RECOMMENDATIONS FOR ENHANCED CUSTOMER EXPERIENCE
1 24