handson-ml2
PythonDataScienceHandbook
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handson-ml2
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Book recommendations for 18yo
A text on applied data science, if you like programming and diving into datasets, this could be a good thing to have, there's a pretty good one that's free on github here.
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Moving to TensorFlow from PyTorch
I'd recommend a skim through the Keras/TensorFlow portion of Hands-On-Machine-Learning-with-Scikit-Learn-Keras-and-Tensorflow (https://github.com/ageron/handson-ml2)
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Hands-on ML with Scikit-Learn, Keras and TF2 - Aurelien Geron (Details in comment)
Here's the GitHub repo for the 2nd Ed.
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It was exactly 2 years ago when I decided to self-study data analytics and now I accepted a 6-digit offer.
Hands-on machine learning (Python): Python reference for machine learning. Use their Github repo as a supplement because some codes in the book are outdated. Finish at least part 1: Fundamentals of machine learning.
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I want to relearn machine learning
You get access from the github, https://github.com/ageron/handson-ml2 Its free, but wont have much context without the book(also "free" at Libgen.is)
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Tensorflow error "W tensorflow/core/data/root_dataset.cc:163] Optimization loop failed: CANCELLED: Operation was cancelled"
Here is the repository.
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NLP resources
I remember an NLP course on DataCamp being helpful as an intro, but a resource I keep handy is Hands-On Machine Learning (Geron) which has really helpful follow along notebooks on the git. Then when you want some background: Deep Learning (Goodfellow)
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An OpenAI Gym docker that can render on Windows
example/18_reinforcement_learning.ipynb: This is a copy from Chapter 18 in Géron, Aurélien's book: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Source code is here in GitHub.
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[D] Thoughts on Hands-On Machine Learning with Scikit-Learn, Keras & Tensorflow by Geron
Have you tried looking at the accompanying github repo.
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[D] Looking for good refreshers on stats / ML to go back to the ML engineer interview game after 2 years doing mostly Software.
Much of the material from that book is publicly available in this repo maintained by the author.
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?
mit-deep-learning-book-pdf - MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
django-livereload-server - Livereload functionality integrated with your Django development environment.
ggplot2-book - ggplot2: elegant graphics for data analysis
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
MLflow - Open source platform for the machine learning lifecycle
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
tests-as-linear - Common statistical tests are linear models (or: how to teach stats)
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
devdocs - API Documentation Browser
react-bits - ✨ React patterns, techniques, tips and tricks ✨
scikit-learn - scikit-learn: machine learning in Python