This is a coursework on foundations of computing module
Through this coursework i worked on methods and classes in python. This was done by analysing some cryptocurrency data and creating a linear regression to predict cryptocurrency prices in the future.
i hope you enjoy it
fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa
End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past
Bottleneck Bottleneck is a collection of fast, NaN-aware NumPy array functions written in C. As one example, to check if a np.array has any NaNs using
In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very length
Simple-Classifier This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example as
KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:
This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d
This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P
Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length
This is the material used in my free Persian course: Machine Learning with Python
ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. It has a simple, flexible syntax, is cloud and tool agnostic, and has interfaces/abstraction
kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from
metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your
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