Tag: machinelearning

  • A Comparison of Binary Classifiers for Enhanced ML/AI Breast Cancer Diagnostics – 1. Scikit-Plot

    A Comparison of Binary Classifiers for Enhanced ML/AI Breast Cancer Diagnostics – 1. Scikit-Plot

    The post compares binary classifiers in Scikit-Learn using the breast cancer dataset. It includes data analysis, ML preparation, learning curves, feature dominance, calibration curves, confusion matrix, ROC curve, precision-recall curve, KS statistic, cumulative gains, lift curves, PCA, and classification reports. Various models’ performances are compared with focus on key metrics and feature evaluations.

  • Build A Simple NLP/NLTK Chatbot

    Build A Simple NLP/NLTK Chatbot

    Chatbots are computer programs that automate conversations with users, providing real-time customer support and industry-specific solutions. This example demonstrates creating a chatbot using Python within Jupyter IDE and implementing simple dialogue. Chatbots are widely used in digital marketing for various business applications, such as customer service, sales, FAQ, shopping, and marketing.

  • DL-Assisted ECG/EKG Anomaly Detection using LSTM Autoencoder

    DL-Assisted ECG/EKG Anomaly Detection using LSTM Autoencoder

    This project implements an ECG anomaly detection framework using an LSTM Autoencoder to accurately identify abnormal ECG events. It trains the autoencoder on normal rhythms, using reconstruction errors to identify anomalies. The proposed method aims to improve abnormal ECG detection, as demonstrated by test results on the ECG5000 dataset, providing valuable information for patient health…

  • DOGE-INR Price Prediction Backtesting

    DOGE-INR Price Prediction Backtesting

    Featured Photo by Rūdolfs Klintsons Let’s look at the Dogecoin: Dogecoin is trading at 0.0666 as of the 13th of March 2023, a 0.91% increase since the beginning of the trading day. Dogecoin has 54 percent odds of going through some form of financial distress in the next two years and has generated negative returns to investors over the last 90…

  • ML/AI Breast Cancer Diagnosis with 98% Confidence

    ML/AI Breast Cancer Diagnosis with 98% Confidence

    We demonstrate the importance of hyperparameter optimization (HPO) for enhancing ML prediction accuracy. Specifically, we will focus on the Random Forest Classifier (RFC) as an ensemble of decision trees. RFC is a supervised ML algorithm that has been applied successfully to the BC binary classification. 

  • Cloud-Native Tech Autumn 2022 Fair

    Cloud-Native Tech Autumn 2022 Fair

    Let’s dive deeper into the cloud-native tech trends and features to follow in Q4 2022 and beyond. Contents: Markets Services Serverless Cybersecurity DevSecOps ML/AI/IoT Use-Cases Events Training Explore More Infographic

  • Breast Cancer ML Classification – Logistic Regression vs Gradient Boosting with Hyperparameter Optimization (HPO)

    Breast Cancer ML Classification – Logistic Regression vs Gradient Boosting with Hyperparameter Optimization (HPO)

    Breast Cancer (BC) is the leading cause of death among women worldwide. The present study optimizes the use of supervised Machine Learning (ML) algorithms for detecting, analyzing, and classifying BC. We compare Logistic Regression (LR) against Gradient Boosting (GB) Classifier within the Hyperparameter Optimization (HPO) loop given by GridSearchCV. We use the publicly available BC dataset…

  • BTC-USD Price Prediction with LSTM

    BTC-USD Price Prediction with LSTM

    The objective of this project is to test the deep learning algorithm of real-time BTC-USD price prediction. We trained the 2-layers Long Short Term Memory Neural Network using Bitcoin Historical Data. The trained LSTM model can be used to predict future price movements of bitcoin.  RMSE ~ $64, with the mean price of $20k (Oct…

  • A Comparative Analysis of Breast Cancer ML/AI Binary Classifications

    A Comparative Analysis of Breast Cancer ML/AI Binary Classifications

    This study is dedicated to #BreastCancerAwarenessMonth2022 #breastcancer #BreastCancerDay @Breastcancerorg @BCAction @BCRFcure @NBCF @LivingBeyondBC @breastcancer @TheBreastCancer @thepinkribbon @BreastCancerNow. One of the most common cancer types is breast cancer (BC), and early diagnosis is the most important thing in its treatment. Recent studies have shown that BC can be accurately predicted and diagnosed using machine learning (ML) technology. Our…

  • Power BI for Data Scientists

    Power BI for Data Scientists

    Power BI is a business analytics tool that provides interactive data visualization capabilities, advanced analytics, and artificial intelligence. Power BI’s AI features include image recognition, text analytics, key driver analysis, and machine learning model building. It offers cloud-based services and a desktop-based interface, allowing data preparation, data discovery, and interactive dashboarding. Supported by Windows, Android,…

  • Technology Focus Weekly Update 16 Oct ’22

    Technology Focus Weekly Update 16 Oct ’22

    Get top data-driven technology highlights of the week: new SaaS products, tech business applications and learnings of the week: DevOps, DevSecOps, Cybersecurity, public cloud platforms (AWS/GCP/Azure), MarTech, ML/AI, MLOPs, NLP, edtech, e-courses, upcoming events, and related Infographics. Contents: DevOps November 8th, 2022     |     11 a.m. ET Providing reliable and secure services doesn’t just happen.  Traditionally,…

  • A Comparison of ML/AI Diabetes-2 Binary Classification Algorithms

    A Comparison of ML/AI Diabetes-2 Binary Classification Algorithms

    The post discusses the increasing urgency to diagnose and treat Type-2 Diabetes (T2D), particularly in developing nations. It delves into the use of data-driven techniques, including ML/AI, in processing T2D data. Different ML/AI methods including DNN, SVM, and DT are applied to the Kaggle PIMA Indian Diabetes (PID) dataset, and performance is assessed using Python…

  • HPO-Tuned ML Diabetes-2 Prediction

    HPO-Tuned ML Diabetes-2 Prediction

    The blog details the author’s tests with machine learning (ML) for enhanced prediction of Type-2 diabetes. The workflows used include RandomizedSearchCV HPO, accuracy metrics, and cross-validation. The post provides in-depth analysis and comparisons of different ML algorithms, such as RandomForestClassifier, GaussianNB, and DecisionTreeClassifier. The experiment findings indicate that RandomForestClassifier with RandomizedSearchCV provides the highest accuracy,…

  • ML/AI Credit Risk Analytics

    ML/AI Credit Risk Analytics

    This project utilized a variety of machine learning algorithms (RF, KNN, DT, GB, LR, ANN, and SVM) to create credit risk modeling for efficient credit rating. Among these, the Gradient Boosting algorithm showed the highest test accuracy at 81.7%. The project also produced feature importance coefficients that reflect relevant credit ratings or probability of default,…

  • The MobiDev ML Approach to Demand Forecasting Demystified

    The MobiDev ML Approach to Demand Forecasting Demystified

    This post outlines MobiDev’s machine learning framework for marketing-driven demand forecasting (DF), consisting of five steps. The process begins with an overview of input data and setting KPIs, followed by data preparation and exploratory analysis. DF models are then trained, tested, and cross-validated, concluding with their final deployment. The approach incorporates business-specific factors like product…

  • ML/AI Diamond Price Prediction with R

    ML/AI Diamond Price Prediction with R

    The post discusses an analysis for determining the price of diamonds, aiming to detect possible overpayment. Using R Studio and various machine learning models, including linear regression, XGBoost, SVM, Decision Tree, and Random Forest, the study targets diamonds’ price and related factors. The best performance is provided by the Random Forest model, indicating the primary…

  • US Real Estate – Harnessing the Power of AI

    US Real Estate – Harnessing the Power of AI

    The content describes a continuation of the use-case series dedicated to real estate (RE) monitoring, trend analysis, and forecast. It focuses on predicting and estimating US house prices using a pre-trained ML model. The content covers various machine learning algorithms, data preprocessing, model training, and evaluation using the Boston housing price dataset. Key takeaways include…

  • Cloud-Native Tech Status Update Q3 2022

    Cloud-Native Tech Status Update Q3 2022

    Cloud Computing Trends Q3 2022, market Share update key services IaaS PaaS FaaS Saas Cloud digital transformation all-the-way DevSecOps CI/Cd GitLab MLOps IoT Tech GCP gateway Big data Deloitte use-cases Stock markets Health Tech Cybersecurity Highlights Events Webinars AWS Storage E-training

  • 10 AI-Powered Websites for Content Writers

    10 AI-Powered Websites for Content Writers

    The content introduces ten innovative AI-powered websites, including Magic Eraser for image editing, Craiyon for AI-generated drawings, Rytr for fast content creation, Thing Translator for language translation via images, AutoDraw for automatic sketching, Fontjoy for AI-based font pairing, Talk to Books for referencing a collection of over 100,000 books, ‘This Person Does Not Exist’ for…

  • ML/AI Wildfire Prediction using Remote Sensing Data

    ML/AI Wildfire Prediction using Remote Sensing Data

    The content is a detailed exploration into the application of machine learning (ML) and artificial intelligence (AI) in predicting wildfires using a dataset acquired in Canada. It covers data preprocessing, ML workflow, exploratory data analysis (EDA), model training, performance evaluation, hyperparameter optimization (HPO), and data resampling techniques like SMOTE and ADASYN. The ML models are…