Practical Machine Learning Coursera
-
Updated
Jun 21, 2014 - R
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Practical Machine Learning Coursera
Performs OCR on the MNIST dataset. From my BSc. AI & Robotics at Prifysgol Aberystwyth
Binary spam classifier in e-mails. It is based on the classification of text using a Naive Bayesian Classifier. The algorithm was written in R.
Final Project for Brad Pasanek's "Hacking for Humanists"--UVA ENSP 3599 Fall 2015.
Bitcoin Price Prediction with 16 Machine Learning Algorithms. The datasets are given. To pull tweets use 'TweetsPull' class. In that case you have to authenticate with your twitter account. The workflow is 1.Pull tweets 2.calculate sentiment score 3.use machine learning algorithms to predict bitcoin price change according to sentiment. This proj…
machine learning with Spark -R implementation. SVM is used to identify the handwritten numbers. Liner regression is used to find out/predict house price. Supervised learning.Linear regression for regression problems. Random forest for classification and regression problems. Support vector machines for classification problems.
Code of the first week of the challenge
Snippets of code for solving common Data Science challenges by using R.
Resample, parameter tuning, meta-learning, clustering, and mining algorithms for the purpose of data mining and machine learning.
analytica vidhya 2018 competition -principal component analysis
Case studies for testing the risk of overfitting and the need for variable selection in spatial (-temporal) predictive modelling
factor selection, exploratory data analysis, statistical learning on both qualitative and quantitative data in R
Data Science tutorial
Solving Real word problems using R programming
Scripts and functions for a monitoring of air temperature in Antarctica using MODIS data and machine learning
anomaly detection with anomalize and Google Trends data
AWS Machine Learning Client