deep-learning-with-r-notebooks
algs4
deep-learning-with-r-notebooks | algs4 | |
---|---|---|
1 | 95 | |
- | 52 | |
- | - | |
- | 0.0 | |
- | about 10 years ago | |
C# | ||
- | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deep-learning-with-r-notebooks
algs4
- Python DSA
-
CS2030S and CS2040S advice
Accompanying resources for the Sedgewick and Wayne Algorithms book at https://algs4.cs.princeton.edu/home/. There are quite a number of examples and exercises for you to go through that lean more towards implementation. I usually recommend to at least go through CLRS or your lecture notes before looking at this.
- Anyone Know resources like (The Odin Project or FullStack open ) but for DSA.
- Ask HN: What is your favorite textbook ever and why?
-
Where can I Learn data structures & algorithms using C++?
I agreed. CLRS is not beginner friendly and really hard to follow if the reader does not have some background prior to reading the book. Algorithms by Sedgewick is much better, his course on Coursera (although the implementation is in Java) is much more intuitive. Programming Abstraction in C++ is also pretty good.
- Textual resources for learning Data Structures and Algorithms
-
Java-based Data Structures class?
Algorithms 4th Edition
- [Computer Science] Algorithms
-
How should I optimise memory of code on Leetcode
Try reading this book or any other source available to you.
-
Grokking Algorithms vs The Algorithm Design Manuel vs A Common-Sense Guide to Data Structures and Algorithms
I recommend Sedgewick’s course and book if you’re serious about it.
What are some alternatives?
algs4 - Algorithms, 4th edition textbook libraries
Reddit-wiki-programming - Resources to Learn Data Structures and Algorithms, ace competitive programming, Get a Job in Tech/CS
Grokking-the-Coding-Interview-Patterns - This course categorizes coding interview problems into a set of 16 patterns. Each pattern will be a complete tool - consisting of data structures, algorithms, and analysis techniques - to solve a specific category of problems. The goal is to develop an understanding of the underlying pattern, so that, we can apply that pattern to solve other problems. [UnavailableForLegalReasons - Repository access blocked]
Crafting Interpreters - Repository for the book "Crafting Interpreters"
Design Patterns - Design patterns implemented in Java
dmca - Repository with text of DMCA takedown notices as received. GitHub does not endorse or adopt any assertion contained in the following notices. Users identified in the notices are presumed innocent until proven guilty. Additional information about our DMCA policy can be found at
git-internals-pdf - PDF on Git Internals
gradle-lint-plugin - A pluggable and configurable linter tool for identifying and reporting on patterns of misuse or deprecations in Gradle scripts.
full-speed-python - Full Speed Python: a book for self-learners
handsonscala - Discussion and and code examples for the book Hands-on Scala Programming
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
Kalman-and-Bayesian-Filters-in-Python - Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.