|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Flatiron School Data Science Curriculum Resources||75||2 years ago||Jupyter Notebook|
|Lesson material on data science and machine learning topics/concepts|
|Neural Network From Scratch||38||a year ago||Rust|
|A neural network library written from scratch in Rust along with a web-based application for building + training neural networks + visualizing their outputs|
|Edx Scalable Machine Learning||7||8 years ago||Python|
|Dslr||3||2 years ago||Python|
|Harry Potter and a Data Scientist: Write a multi-class classifier using gradient descent optimization algorithm to replace the bewitched Sorting Hat and save Hogwarts! 🎩🧙♂️|
|The Essential Guide To Calculus For Ml||2||a month ago||Jupyter Notebook|
|This is a comprehensive and beginner-friendly repository that covers the basics of Calculus and its applications in Machine Learning, including topics such as Differentiation, Integration, Vector Calculus, Optimization Algorithms, and more.|
|Covid 19_modelling_for_india||1||2 years ago||Jupyter Notebook|
|Modelling the Coronavirus Statistics for India using the SIR Model|
|Microsoft Dat256x Essential Math For Machine Learning Python Edition||1||2 years ago||Jupyter Notebook|
|Machine learning and AI are built on mathematical principles like Calculus, Linear Algebra, Probability, Statistics, and Optimization. This course aims to help you learn some essential foundational concepts and the notation used to express them.|
On no! Since its creation, the famous school of wizards, Hogwarts, had never known such an offense. The forces of evil have bewitched the Sorting Hat. It no longer responds, and is unable to fulfill his role of sorting the students to the houses.
The new academic year is approaching. Gladly, the Professor McGonagall was able to take action in such a stressful situation, since it is impossible for Hogwarts not to welcome new students. . . She decided to call on you, a muggle "datascientist" who is able to create miracles with the tool which all muggles know how to use: a "computer". Despite the intrinsic reluctance of many wizards, the director of the school welcomes you to his office to explain the situation. You are here because his informant discovered that you are able to recreate a magic Sorting Hat using your muggle tools.
You explain to him that in order for your "muggle" tools to work, you need students data. Hesitantly, Professor McGonagall gives you a dusty spellbook. Fortunately for you, a simple "Digitalis!" and the book turned into a USB stick.
Which Hogwarts course has a homogeneous score distribution between all four houses ?
What are the two features that are similar ?
Some features are homogenous or coherant with other ones, so there existance is not necessary for training the model and can give use= a complex hypothesis that will cause 'Overfitting' Our choice was to remove:
python3 logreg_train.py [-BGD | -SGD] <_train dataset_>
Output a file named: ./weights.csv that contain the weights of the model.
In the end of the training the program output the: (using the training set)
python3 logreg_predict.py [-p] <_dataset_> <_weights_>
Output a file named: ./houses.csv that contain the Indexs and the predicted house affected to the students.
pip3 install pandas
pip3 install matplotlib
pip3 install seaborn