aligeekk Goto Github PK

followers: 1.0 following: 2.0 repos: 293.0 gists: 1.0

Type: User

aligeekk's Projects

lending_club_loan_status_prediction

LENDING CLUB - Loan Status Prediction| Tools Used: Python, Scikit Learn, Pandas

loan-picker

Web app providing analysis and predictive modeling of peer-to-peer lending data

Classification between good and bad loan requests based on loan data for year 2013-2014 from Lending Club (https://www.lendingclub.com/info/download-data.action) that'll help investors in deciding which loans they should invest

loandefault-prediction

Lending Club Loan data analysis

loanprediction-using-decision-trees

Attempted to predict the current status of loan to a given borrower by using Lending club lone data set using decision tree classifier (scikit-learn).The loan data records with title field of credit card, medical and debt are used. A loan status category of 0 is considered to be good because the loan status is either Fully Paid or Current. A loan status category of 1 is considered to be poor because the loan status is either Late(for any time period) or charged off .Thus we will train our model which will predict the class of the borrower so as to make it easy for the lender to decide the grant of loan

machine-learning

Implementation of different machine learning techniques

machine-learning---intrest-rate-prediction-for-peer-to-peer-lending-group

Machine Laerning - Intrest Rate Prediction for Peer to peer Lending Group

machine-learning-algorithms-for-detecting-network-attacks-with-unsw-nb15-data-set

Due to the increasingly development of network technology recently, there are various cyber-attacks posed the huge threats to different fields around the world. Many studies and researches about cyber-security are carried out by experts in order to construct a safe network environment for people. The aim of the work is to build the detection models for classifying the attack data. Hence, we applied the UNSW-NB15 network data set which combines both normal and modern low-level attacks because we would like to create the experimental scenario close to the real world. Two classifiers are logistic regression and decision tree model for binary classification in the work. The deployed technique for decision tree achieved the highest result with 99.99% of testing accuracy compare to the 78.15% of logistic regression classifier. On the other hand, the KNN model is used for categorizing the multi-class in the project, and the averaged accuracy for testing is around 23% for ten categories classification.

machine-learning-approach-for-malware-detection

A Machine Learning approach for classifying a file as Malicious or Legitimate

machine-learning-based-classification-of-cervical-cancer-using-k-nearest-neighbor-random-forest-and

Cervical cancer is the second most common type of cancer that is found in the women worldwide. Generally, cancer caused due to irregular growth of cells in a particular area that or have the potential to spread to the other parts of the body as well. Identification of a cervical cancer test is an examination of the tissue taken from a particular region, which might contain cancerous cells through biopsy, is exceptionally challenging because these types of cells does not offer unusual color or texture variants from the standard cells. To identify the abnormalities in human cell the high-level digital image processing technologies are already present in the market which very costly concerning the money. Therefore, we are proposing the model which going to classify whether a female patient has cervical cancer or not. We are using various attributes from real-life and performing a feature selection algorithm Recursive Feature Elimination (RFE). Afterward, making classification models using three machine-learning algorithms like K-Nearest Neighbor (KNN), Random Forest and Multilayer Perceptron (MLP), MLP is a type of the Artificial Neural Network (ANN) algorithm whereas KNN and Random Forest is a supervised type of algorithm.

machine-learning-loan-lending-club

Building Classification & Prediction model to classify the Loan applicant request as approved or rejected and then predict the Interest rate for Loan Approval.

machine-learning-malware-detection

Attempt to use the machine learning workflow to process and transform sampled PE file data to create a prediction model.

machine-learning-notebooks

Stanford Machine Learning course exercises implemented with scikit-learn

machine-learning-numpy

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

machine-learning-online-2018

ML Online Course Repository. Course videos on online.codingblocks.com

machine-learning-with-python

Python code for common Machine Learning Algorithms

machinelearning

clustering, regression, classification, deep learning, neural networks, exploratory data analysis, feature selection

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft

machinelearnjs

Machine Learning library for the web and Node.

malicious-url-detection-using-machine-learning

A simple Logistic Regression Alogrithm to classify Malicious Url's

malicious-url-detection-with-ml

Malicious URL Detection Using Machine Learning

malicious_url_detection

malicious url detection using deep learning

maliciousurl

Lexical based Malicious url detection using machine learning algorithm

maliciousurldetection

Using machine learning algorithms to detect and identify malicious URLs

malware-detection

Malware Detection and Classification Using Machine Learning

malware-detection-using-machine-learning

Multi-class malware classification using Deep Learning

matchingalgorithms

My quick take on matching algorithms using RF, XGBoost on an imbalanced dataset.

math-of-machine-learning-course-by-siraj

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

maths-for-ml

Notes and solutions for the Mathematics for Machine Learning Specialization

matlab

Deep Learning using Neural Network Toolbox + Finance Portfolio Selection with MorningStar

aligeekk Goto Github PK

aligeekk's Projects

Recommend Projects

Recommend Topics

Recommend Org

Jobs