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deep-reinforcement-learning

A repository to understand the application of Reinforcement Learning (Deep Q Learning) on Game Optimization

deep_q_learning

This is the Code for "Deep Q Learning - The Math of Intelligence #9" By Siraj Raval on Youtube

deeplearning

repo for work in deep learning (no reinforcement learning here)

deeppy

Deep learning in Python

default-loan

Predicting Loan Status

detect_phishing_website

Detecting phishing website using machine learning

detecting-a-phishing-url-by-machine-learning

Here, in this Repository lies a Machine Learning Project which can Detect Phishing URL. It takes an URL as Input and Detects that if it is Phishing URL or not and Generates Output respectively. Good for "not phishing url" and Bad for for "phishing url".

detecting-phishing-attacks-using-ml

detecting-phishing-url-by-ml-and-nlp

In this project we detect Phishing URL by Machine Learning and Natural Language Processing techniques.

detecting-phishing-websites

detecting phishing websites using machine learning

detection-of-advertisement-through-machine-learning-approach

Classification of Advertisement URL using Machine Learning.

dfa-detection

Metamorphic Viruses Analysis and Detection by "DFA-Detection" Algorithm

document-similarity

Similarity between two documents using various measures like manhattan distance, euclidean distance, supremum distance, cosine similarity and PCA.

drivendata--heart-desease-prediction

dsc-3-28-11-graph-dynamics-bipartite-graphs-lab-online-ds-sp-000

easy-scraping-tutorial

Simple but useful Python web scraping tutorial code.

effective-pandas

Source code for my collection of articles on using pandas.

email-fraud-nlp-

A simple 0️⃣1️⃣ classifier employing various 💬 NLP and text processing 💬 techniques to flag fraudulent 📧

email-phishing-attempts-detection-using-nlp

Email Phishing Attempts Detection from the text of email bodies using natural language processing and machine learning

ensemble-classifier

Deep neural network classifier that uses auto-encoders for feature selection. The primary objective is to evaluate the performance difference between regular classification models with topic modeling and deep neural network with auto-encoders. Tools/technologies used: Scikit-learn, Python machine learning models, Keras

ensemblemethodsforfeatureselection

By applying ensemble methods we improve the robustness of feature selection methods.

fann

Official github repository for Fast Artificial Neural Network Library (FANN)

fastnn

An Artificial Neural Network on Steroids. This network was built to be expandable and versatile while maintaining speed. Try this network compared to python's PyBrain. Right now it has a demo to add 1 to three separate binary numbers.

fcm_fnn

Implementation of Fuzzy Cognitive Maps Based on Fuzzy Neural Network

featselection

Feature selection methods for text classification

feature-engineering-feature-selection-techniques-

Coding an End-To-End Demonstration [Feature Selection Techniques]

feature-selection

Features selector based on the self selected-algorithm, loss function and validation method

feature-selection-1

Feature Selection using Deep Neural Networks

feature-selection-for-machine-learning

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

feature-selection-k-means-and-expected-maximization-for-sgemm-and-australian-weather-dataset

To implement Feature selection, Dimensionality Reduction and use these features in Principal Component Analysis, Independent Component Analysis and Random Component Analysis for K Means, Expected Maximization and Neural network.