ggplot2-book
handson-ml2
ggplot2-book | handson-ml2 | |
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31 | 13 | |
1,588 | 28,327 | |
0.5% | 0.5% | |
0.0 | 0.0 | |
6 months ago | 8 months ago | |
Perl | Jupyter Notebook | |
- | Apache License 2.0 |
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ggplot2-book
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Does anyone else absolutely love plotting their data
I also only recently started using ggplot after doing most of my graphs with base R‘s plot() function. I started by reading ggplot2 by Hadley Wickham which is also available as a free ebook. Reading the first few chapters is enough to enable you to plot many basic plots. I can’t imagine going back to any other visualization tool ever again. Absolutely love the freedom ggplot gives you.
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I am starting to learn R and I love it. I would like to learn at least 1 another simmilar language. Which one(s) should I learn?
His ggplot book will teach you all you need to know about R plotting, and is probably right at your current level. It is likewise pretty great, ggplot
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What are your favorite softwares for data visualization?
The OG book is still the best in my opinion! https://ggplot2-book.org/
- Data analysis skills before/in lieu of master’s program
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How can I do this graph?
You could use base R, see ?plot but a lot of people would use ggplot2. However, looking at your data it won’t look very good because there’s going to be very few points per country.
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Can someone explain how R project are organized and deployed?
If you included DESCRIPTION to your repository (like in ggplot2-book - https://github.com/hadley/ggplot2-book/blob/master/DESCRIPTION ) devtools::install_deps() and renv::install() will install dependencies listed there as would pip with requirements.txt , you can trigger this from your R script, from command line or from whatever deployment / automation tool you are using.
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[Q] is majoring in stats a bad choice if i suck at programming?
Chapters 1-8 of https://adv-r.hadley.nz/, https://r4ds.had.co.nz/ , and https://ggplot2-book.org/ were covered in my statistical computing courses. I don't think it gets much more advanced than that at the undergrad level.
- How to add color?
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How can I make a line graph!?
You can check out more about Ggplot2 here: https://ggplot2-book.org/
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Ask HN: How would you spatialize higher dimensional data?
* "ggplot2: Elegant graphics for data analysis" : https://ggplot2-book.org/
handson-ml2
- Learn Machine Learning with these GitHub repositories
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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.
What are some alternatives?
r4ds - R for data science: a book
mit-deep-learning-book-pdf - MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
cheatsheets - Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
tests-as-linear - Common statistical tests are linear models (or: how to teach stats)
mech - 🦾 Mech is a programming language for building data-driven systems like robots, games, and interfaces. Start here!
MLflow - Open source platform for the machine learning lifecycle
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)
PythonDataScienceHandbook - Python Data Science Handbook: full text in Jupyter Notebooks
tidyr - Tidy Messy Data
dtplyr - Data table backend for dplyr
data_to_viz - Leading to the dataviz you need
Frustration-One-Year-With-R - An extremely long review of R.