deeplearning-notes
PythonDataScienceHandbook
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MIT License | MIT License |
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deeplearning-notes
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Intuition for LSTM cell structure
If you want in-depth understanding then I would recommend you to look for Deep Learning Specialization by Andrew Ng. (Course 4). He explained the LSTM and GRU cells in detail (mathematically). You can also find it on YouTube I guess. Hope it helps.
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[D] Best deep learning course?
Best place to get started https://www.coursera.org/specializations/deep-learning
- Which course from deeplearning.ai should I take first? There are so many now
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Where to go from here
I want to expand on what I learnt theory and practice to be able to complete a project, where I can download a video and run it through my model and it will be able highlight specified items, e.g people trees, cars. Will this course help me get there https://www.coursera.org/specializations/deep-learning
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This is my self-learning curriculum for ML. Hope it helps and open to feedback!
Another one from DeepLearning.ai and this is also the most popular course for Deep Learning and Neural Networks - https://www.coursera.org/specializations/deep-learning
- AI roadmap
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Assignments to practice for course "neural-networks-deep-learning"
This course is a part of one of the 5 courses in DL specialization: https://www.coursera.org/specializations/deep-learning. I am taking this course on Coursera where I have finished up to week 2. Now I need to practice for it, but I think I can't access assignments as its locked for paid viewers. Can someone share me the resources for practice or any alternatives you found useful?
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Coursera or Udacity for TF developer certificate
There is another [course] (https://www.coursera.org/specializations/deep-learning) by deeplearning ai that catched my eye and in review they say its more in detail than tf in practice course.
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Career in Computer Vision - Best way to spool up through OMSCS
Deep learning like others said, but I've seen some posts recommending taking an external class, like Andrew Ng's Coursera class https://www.coursera.org/specializations/deep-learning over the GT one. I haven't taken or plan on taking the GT one but some people found it lacking
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How relevant is “A super harsh guide to machine learning” for someone who is just tinkering with machine learning?
My recommendations are worth little, I'm just starting through all this stuff myself. I'm currently taking the Deep Learning specialization on Coursera and trying to map out what else I should be doing.
PythonDataScienceHandbook
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About Data analyst, data scientist and data engineer, resources and experiences
Python Data Science Handbook
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Where to learn data science with python??
Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data
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Book Recommendations
I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.
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Other programing options?
Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)
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Pathways out of GIS?
Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.
- Help a lady out (career advice(
- Resources for Current DE Interested in Learning Data Science
- Good book or course to learn Python for someone who is fluent in R?
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Python equivalent to R's ecosystem of open source educational materials
I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/
What are some alternatives?
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
django-livereload-server - Livereload functionality integrated with your Django development environment.
Credit_Card_Data_Clustering - Using Gaussian Clustering and PCA Techniques to make clusters of the Credit Car data
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
Breast_Cancer_DecisionTree_Classifier
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
ml-coursera-python-assignments - Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
micrograd - A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
NNfSiX - Neural Networks from Scratch in various programming languages
devdocs - API Documentation Browser