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https://github.com/kurianbenoy/learning
https://github.com/kurianbenoy/learning
Last synced: 9 days ago
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- Host: GitHub
- URL: https://github.com/kurianbenoy/learning
- Owner: kurianbenoy
- Created: 2020-08-17T03:28:41.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-02-14T13:42:43.000Z (almost 4 years ago)
- Last Synced: 2024-11-15T03:51:36.998Z (2 months ago)
- Size: 97.7 KB
- Stars: 0
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Learning
- "Learn something new everyday to ignite your inner self"
- What I cannot create, I do not understand
[source- Secret Thoughts of Successfull Hacker](https://www.youtube.com/watch?v=M6xlhTqATyM)
## Buisness Domain knowledge
* Redash
- [x] Getting started - https://redash.io/help/user-guide/getting-started
- [x] Setup - https://redash.io/help/open-source/setup
- [x] Other source - https://fitdevops.in/how-to-setup-redash-dashboard-on-ubuntu/
- [x] Watch [Redash youtube videos](https://www.youtube.com/channel/UCZWXs5WDtDKlmDDX5A84YPQ)
- [x] Create Redash titanic example
- [ ] Create redash application
- [x] [Redash MongoDB page](https://redash.io/help/data-sources/querying/mongodb)
- [ ] Read complete redash user guide
- [x] Querying
- [x] Visualisation
- [x] Dashboard
- [ ] Alerts
- [x] User, groups and permissions
- [x] Data sources and querying
* Mongo DB basics
- [x] [Crash course with mongodb](https://www.youtube.com/watch?v=-56x56UppqQ)
- [x] Mongo DB introduction
- [x] [Structure your data for MongoDB](https://docs.mongodb.com/guides/server/introduction/)
- [x] Mongodb aggregation
- [x] Mongo db documents, datasets
- SQL
- [x] https://www.analyticsvidhya.com/blog/2020/07/8-sql-techniques-data-analysis-analytics-data-science/
- [x] Intro to Kaggle SQL course
- Getting started
- Select, from , where
- Groupby, Having, count
- order by
- as and with
- joining data
- [ ] Advanced Kaggle SQL course
- Join and unions
- Analytic functions
- Nested and repeated data
- Write efficient queries
## Software Engineering
- Docker
- [x] [how-docker-can-help-you-become-a-more-effective-data-scientist](https://towardsdatascience.com/how-docker-can-help-you-become-a-more-effective-data-scientist-7fc048ef91d5)
- [ ] [Docker in action notes](https://notes.hamel.dev/docs/docker/Docker-In-Action.html)
- docker container deletion
> Removes every image/volume/conatiners ---> docker system prune -a, system prune volume
> and to remove only one ---> docker rm ID_or_Name ID_or_Name```
- [x] [Docker filesystem](https://medium.com/@BeNitinAgarwal/docker-containers-filesystem-demystified-b6ed8112a04a)
- [ ] [Docker file storage driver](https://docs.docker.com/storage/storagedriver/)
> sudo docker-compose down --rmi all
- [ ] [Docker-compose 101](https://www.tutorialspoint.com/docker/docker_compose.htm)
- [ ] Docker networks
- [x] [Generators](https://realpython.com/introduction-to-python-generators/)
## Server Side
- [x] [A Guide to ASGI in Django 3.0 and its Performance ](https://arunrocks.com/a-guide-to-asgi-in-django-30-and-its-performance/)
- [ ] [Async Django views](https://arunrocks.com/django-async-views-examples/)
- [x] [Flask RestJSONAPI](https://flask-rest-jsonapi.readthedocs.io/en/latest/)
## Research Papers
- [x] [GPT-2 Language models are unsupervised learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)
- [x] [GPT 3- Language models are few shot learners](https://arxiv.org/abs/2005.14165)
- [X] [Seq2SQL paper](https://arxiv.org/pdf/1709.00103v7.pdf)
- [x] [Bert based Sentiment analysis & key-entity recognition](https://arxiv.org/abs/2001.05326)
- [ ] [Extracting sentiment attitudes from Analytical Text](https://paperswithcode.com/paper/extracting-sentiment-attitudes-from)
- [x] Array programming with numpy
- [x] Efficent Transformers(survey)
- [x] [Multi-entity sentiment analysis using entity-level feature extraction and word embeddings approach](https://www.acl-bg.org/proceedings/2017/RANLP%202017/pdf/RANLP094.pdf)
## Online Course
- CS 229 ML course - Andrew NG
https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
- [x] Lesson 14: Expectation maximisation theoreum ```
- [x] 15: EM Algorithm and factor analysis
- [ ] 16: Independent Component Analysis
- [ ] 17. MDPs and Value Policy iteration
- [ ] 18. Continuos State MDP and model simulation
- [ ] 19. Reward model and linear dynamic system
- [ ] 20. RL Debugging and diagnostics
- Full Stack Deep learning course
- Setting up ML Projects
- [x] Overview
- [x] Lifecycle
- [x] Prioritizing
- [x] Archetypes
- [x] Metrics
- [x] Baselines
- [x] Data Management
- [x] Infrastructure
- [x] ML Teams
- [x] Training
- [ ] Labs
- [ ] Guest Lectures
- FastAI(Practical course for beginners) - 2020
- [ ] Lesson 1
- [ ] Lesson 2
- [ ] Lesson 3
- [ ] Lesson 4
- [ ] Lesson 5
- [ ] Lesson 6
- [ ] Lesson 7
- [ ] Lesson 8
## Books
- Approaching almost any machine learning problems
- [x] Appraching Categorical variables
- [x] Feature Engineering
- [x] Feature selection
- [x] Cross-validation
- [x] Evaluation Metrics
- [x] Supervised vs Unsupervised learning
- [x] Approaching almost any CV problem
- [x] Approaching text classification/regression
- [x] Approaching ensembling and stacking
- [x] Approaching reproducible code & model serving
- [x] Hyperparameter optimization
- [x] Arranging ML projects
## Talks
- [x] [To grandmaster validation strategy & journey](https://kommunity.com/kaggle-days-meetup-istanbul/events/top-grandmasters-kaggle-journeys-and-validation-strategies-8fef83ef)
- [ ] [Talks # 10: Tanishq Abraham; What are CycleGANs? (a novel deep learning tool in pathology)](https://www.youtube.com/watch?v=gT8-wDPLOBg)
- [x] [Becoming hireable as a datascientist 2022 - Ajinkya Kohli](https://www.youtube.com/watch?v=Mas--YzMLwQ)
- [x] [SPACY'S ENTITY RECOGNITION MODEL: incremental parsing with Bloom embeddings & residual CNNs](https://www.youtube.com/watch?v=sqDHBH9IjRU)
- [x] [Art for Tensorflow by Margaret](https://www.youtube.com/watch?v=scICM4A2uMQ)
- [x] [Network like a pro-sanyam](https://www.youtube.com/watch?v=joQ98JUIWV4)
- [x] [Ensembling, Blending and stacking](https://www.youtube.com/watch?v=TuIgtitqJho)
- [x] [The Don'ts of Data Science & Kaggling" with Rohan Rao](https://www.youtube.com/watch?v=SZcuHToDKmk)
- [x] [Inside the Cheeseshop: How Python Packaging Works - Dustin Ingram](https://www.youtube.com/watch?v=AQsZsgJ30AE)
- [x] [Python Packaging - Where We Are and Where We're Headed - Pradyun Gedam ](https://pyvideo.org/pycon-india-2019/python-packaging-where-we-are-and-where-were-headed-pradyun-gedam.html)
- [x] [Secret Thoughts of Successfull Hacker](https://www.youtube.com/watch?v=M6xlhTqATyM)
- [x] [The Path to Mastery - Anand Chitipothu](https://youtu.be/OFKiVEl-cYw)
Mastery is about getting better yourself. Pitfalls like GSoc, Competitive. Think why you are doing? Are you doing for
recognition or because you like it