100 Days of ML Coding
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Updated
Sep 30, 2020
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Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
100 Days of ML Coding
A complete daily plan for studying to become a machine learning engineer.
The "Python Machine Learning (1st edition)" book code repository and info resource
What would you like to be added: As title
Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.
**Without this feature, how does current nni
Minimal and clean examples of machine learning algorithms implementations
手写实现李航《统计学习方法》书中全部算法
Tick-Tack-Toe game is not working for exception part
Else part on line 247 takes you to infinite loop on getting any char value as input for position.
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Current default value for rows_per_chunk parameter of the CSV writer is 8, which means that the input table is by default broken into many small slices that are written out sequentially. This reduces the performance by an order on magnitude in some cases.
In Python layer, the default is the number of rows (i.e. write table out in a single pass). We can follow this by setting rows_per_chunk
Plain python implementations of basic machine learning algorithms
https://igel.readthedocs.io/en/latest/_sources/readme.rst.txt includes a link to the assets/igel-help.gif, but that path is broken on readthedocs.
readme.rst is included as ../readme.rst in the sphinx build.
The gifs are in asses/igel-help.gif
The sphinx build needs to point to the asset directory, absolutely:
.. image:: /assets/igel-help.gif
I haven't made a patch, because I haven't
We do not have documentation specifying the different treelite Operator values that FIL supports. (https://github.com/dmlc/treelite/blob/46c8390aed4491ea97a017d447f921efef9f03ef/include/treelite/base.h#L40)
Report needed documentation
https://github.com/rapidsai/cuml/blob/branch-0.15/cpp/test/sg/fil_test.cu
There are multiple places in the fil_test.cu file
A high performance implementation of HDBSCAN clustering.
I'm sorry if I missed this functionality, but CLI version hasn't it for sure (I saw the related code only in generate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.
Of course, piping is a solution, but not for development in Jupyter Notebook, for example.
Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.
This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)
Hi, Thanks for the awesome library!
So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).
I conceptually
The standard package for machine learning with noisy labels and finding mislabeled data in Python.
The Python code to reproduce the illustrations from The Hundred-Page Machine Learning Book.
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
A modular active learning framework for Python
2020年的算法实习岗位/校招公司信息表,部分包括内推码,和常见深度学习基础知识笔记、算法岗面试题答案,及暑期计算机视觉实习面经和总结。
This Pull Request is for HacktoberFest 2020
Description of Change
Checklist