| Avik-Jain/100-Days-Of-ML-Code |
42,417 |
|
0 |
0 |
over 2 years ago |
0 |
|
60 |
mit |
|
| 100 Days of ML Coding |
| rasbt/python-machine-learning-book |
11,645 |
|
0 |
0 |
over 3 years ago |
0 |
|
11 |
mit |
Jupyter Notebook |
| The "Python Machine Learning (1st edition)" book code repository and info resource |
| BinRoot/TensorFlow-Book |
4,443 |
|
0 |
0 |
over 6 years ago |
0 |
|
14 |
mit |
Jupyter Notebook |
| Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations. |
| zotroneneis/machine_learning_basics |
3,754 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Plain python implementations of basic machine learning algorithms |
| BoltzmannEntropy/interviews.ai |
3,146 |
|
0 |
0 |
about 4 years ago |
0 |
|
4 |
|
|
| It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well. |
| greyhatguy007/Machine-Learning-Specialization-Coursera |
2,082 |
|
0 |
0 |
over 2 years ago |
0 |
|
16 |
mit |
Jupyter Notebook |
| Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG |
| justmarkham/DAT8 |
1,549 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| General Assembly's 2015 Data Science course in Washington, DC |
| ibrahimjelliti/Deeplearning.ai-Natural-Language-Processing-Specialization |
523 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
gpl-3.0 |
Jupyter Notebook |
| This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai |
| hollance/TensorFlow-iOS-Example |
420 |
|
0 |
0 |
about 9 years ago |
0 |
|
8 |
|
Swift |
| Source code for my blog post "Getting started with TensorFlow on iOS" |
| kanyun-inc/ytk-learn |
351 |
|
0 |
0 |
almost 4 years ago |
0 |
|
|
mit |
Java |
| Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax). |
