learning
ML-University
learning | ML-University | |
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3 | 6 | |
6,092 | 794 | |
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8.1 | 3.4 | |
7 days ago | 7 months ago | |
HTML | ||
MIT License | - |
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learning
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A Clear roadmap to complete learning AI/ML by the end of 2022 from ZERO
Not exactly a roadmap, but I documented my learning journey here: https://github.com/amitness/learning
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[D] How software engineer get into machine learning job role?
My general transition occurred as follows: 2017-2018: - Worked as full-stack web developer in Python + Angular. Worked with a stack that had some overlap with ML Engineering (Flask, AWS Services, SQL) - In the weekends and evenings, I started doing MOOCs + practicing tons of ML. The courses I follow are here. My focus was both to go broad first and then slowly dive deep.
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Resources for self-study NLP
Personally, I'm following this to get good at NLP: https://github.com/amitness/learning#be-able-to-implement-nlp-models
ML-University
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Daily Ask Anything: 2022-07-18
For ML: Free ML University is a fantastic resource. I also really like Andrew Ng's courses on Coursera.
- From where can I learn Data Science?
- A Clear roadmap to complete learning AI/ML by the end of 2022 from ZERO
- What to learn next?
- How to start learning ML
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Free resource for Learning Machine Learning/ DL / NLP
Here is the link for the same repo: ML-University
What are some alternatives?
udacimak - Udacity Nanodegree and Course Downloader
ai-deadlines - :alarm_clock: AI conference deadline countdowns
udacity-nanodegrees - :mortar_board: List of Udacity Nanodegree programs with links to the free courses in their curricula
overlays - MarketerBay Overlays. Sandbox open source projects.
udacity-nanodegree-react - Study notes and projects from the Udacity's React Nanodegree program
Awesome-Diffusion-Models - A collection of resources and papers on Diffusion Models
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
golang-training - Golang for Backend Developer with Nordic Coder
CS7038-Malware-Analysis - Course Repository for University of Cincinnati Malware Analysis Class (CS[567]038)
Recognition-of-logical-document-structures - First approach for recognizing logical document structures like texts, sentences, segments, words, chars and sentence/segment depth based on recurrent neural network grammars.
UBB-INFO - All projects from university.
resources - Resources on various topics being worked on at IvLabs