Focused crawls are collections of frequently-updated webcrawl data from narrow (as opposed to broad or wide) web crawls, often focused on a single domain or subdomain.
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
NVIDIA GPU-Accelerated Deep Learning. Reinforcement learning (RL) implementation of imperfect information Chinese game Mahjong. Markov decision processes to predict future Mahjong states
The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.
This is a supervised Recurrent Neural Network (RNN) learning project treating stock trading as a classification problem. Given input of a 60 day window of pricing data, choose the best action for maximum profit. This uses my earlier https://github.com/TimRivoli/Stock-Price-Trade-Analyzer project for a trading environment, and its SeriesPrediction module for data preparation and model training.
