15

Machine Learning Useful Links

 4 years ago
source link: http://uzairadamjee.com/blog/machine-learning-guide/
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
neoserver,ios ssh client

Machine Learning Useful LinksSkip to content

python_tips.jpeg

Machine Learning Useful Links

September 18, 2020 uzairadamjee 0 Comments

In this guide I am sharing some useful links related to Machine Learning and Algorithms. These tutorial will help anyone preparing for ML algorithm or learning about ML in general.

Machine Learning:
https://www.edureka.co/blog/interview-questions/machine-learning-interview-questions/

https://www.springboard.com/blog/machine-learning-interview-questions/

https://www.analyticsvidhya.com/blog/2016/09/40-interview-questions-asked-at-startups-in-machine-learning-data-science/

Confusion Matrix:
https://towardsdatascience.com/beyond-accuracy-precision-and-recall-3da06bea9f6c

https://www.kdnuggets.com/2020/01/guide-precision-recall-confusion-matrix.html#:

Logistic Regression:

https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python

Decision Tree:

https://www.edureka.co/blog/decision-trees/

https://www.geeksforgeeks.org/decision-tree-introduction-example/

Random Forest:

https://towardsdatascience.com/an-implementation-and-explanation-of-the-random-forest-in-python-77bf308a9b76

https://www.analyticsvidhya.com/blog/2015/06/tuning-random-forest-model/#:~:text=n_estimators%20%3A,but%20makes%20your%20code%20slower.

Naive Bayes:

https://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/#:~:text=It%20is%20a%20classification%20technique,presence%20of%20any%20other%20feature.

https://www.geeksforgeeks.org/naive-bayes-classifiers/

K-Nearest Neighbor:

https://www.kdnuggets.com/2020/04/introduction-k-nearest-neighbour-algorithm-using-examples.html

https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_knn_algorithm_finding_nearest_neighbors.htm

https://towardsdatascience.com/machine-learning-basics-with-the-k-nearest-neighbors-algorithm-6a6e71d01761#:~:text=Summary-,The%20k%2Dnearest%20neighbors%20(KNN)%20algorithm%20is%20a%20simple,both%20classification%20and%20regression%20problems.&text=Finally%2C%20we%20looked%20at%20an,an%20application%20of%20KNN%2Dsearch.

Neural Networks:

https://towardsdatascience.com/machine-learning-for-beginners-an-introduction-to-neural-networks-d49f22d238f9

A/B Testing:

https://medium.com/@robbiegeoghegan/implementing-a-b-tests-in-python-514e9eb5b3a1

This guide wiil help you out in many way, I used it so I thought its a good time to share it with other. If you want to add something do let me know in comment. Thanks!


Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Comment

Name *

Email *

Website

Save my name, email, and website in this browser for the next time I comment.

Post navigation

Stay up to date

Name
Email*

TechCrunch


About Joyk


Aggregate valuable and interesting links.
Joyk means Joy of geeK