All codes, both created and optimized for best results from the SuperDataScience Course
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Updated
Nov 5, 2017 - Python
All codes, both created and optimized for best results from the SuperDataScience Course
Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and s…
Harvard Project - Accuracy improvement by adding seasonality premium pricing
Deteksi penyakit pada (daun) jagung berbasis citra dengan menggunakan metode GLRLM dan FCH.
A JavaScript module for generating random seeded distributions and its statistical analysis.
A minimal Deep learning library for the web.
Spark ML Dashboard built to plug-in and tweak the model params to real-time verify classification results on sample test data
Predict the type of arrhythmia based on Electro-cardiogram (ECG) tool using machine learning models and algorithms.
Classic Machine Learning in R
In this project using New York dataset we will predict the fare price of next trip. The dataset can be downloaded from https://www.kaggle.com/kentonnlp/2014-new-york-city-taxi-trips The dataset contains 2 Crore records and 8 features along with GPS coordinates of pickup and dropoff
This is the code for "Binary Classification using Keras Sequential, Functional and Model Subclassing" By M.Junaid Fiaz
Capstone Project for Udacity Machine Learning Nanodegree
Master's Thesis project at University of Agder, Spring 2020. Classification with Tsetlin Machine on board game 'GO'.
Face Mask Detection
Google colab notebook for the Kaggle Home prices submission
Python and sklearn, KNN, logistic and linear regression, cross-validation
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