Category: Uncategorized
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A Comparative Analysis of The 3 Best U.S. Growth Stocks in Q1’23 – 3. LYTS
Featured Photo by Pixabay Table of Contents SeekingAlpha The peer-to-peer LYTS comparison table is as follows with the 1Y price return chart LSI Industries: Impressive Q1 Results With Significant Growth Prospects StockNews TradingView 1Y LYTS stock price USD with Bollinger Bands strategy, Stochastic Oscillator (SO) and the market cap (MC). The 1-week technical analysis summary…
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Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing
The Fashion MNIST Dataset Fashion-MNIST is a dataset of Zalando’s article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28×28 grayscale image, associated with a label from 10 classes: Each image pixel has a single pixel-value associated with it, indicating the lightness or darkness…
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ECG Early Warning System (EWS) in Terms of the Heart Stress-Strain Failure Curve
Featured Photo by Anna Shvets on Pexels Explore More AI-Based ECG Recognition – EOY ’22 Status ML-Assisted ECG/EKG Anomaly Detection using LSTM Autoencoder Embed Socials Infographic
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ML/AI Prediction of Wine Quality
As Goethe once said, “Life is too short to drink bad wine.” Predicting wine quality using ML/AI techniques is becoming increasingly popular today. ML models can tell us exactly what makes a good quality wine. Today we will compare the key multi-label classifiers used for wine quality prediction in ML algorithms. Our specific goals are as…
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COVID-19 Geospatial Data Visualization with Plotly, Geopandas, and Folium
Featured Photo by Andrea Piacquadio on Pexels The rapid diffusion of COVID-19 and data convenience had enforced the global community to work more vigorously on geospatial analysis of this pandemic. This is a shining moment for GIS: responding to COVID-19 with maps and data-smart city solutions. Best Practices: In New Zealand, residents can stay abreast…
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Comparing 4 Python Libraries for Interactive COVID-19 Data Science Visualization
Featured Photo by Polina Zimmerman on Pexels. Data Visualization (DV) is the first step towards getting an insight into a large data set in every data science project. DV tools available in Python can be a very effective and efficient way of finding trends, outliers, and hidden patterns in data. Following the recent DV study…
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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…
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AI-Driven Skin Cancer Diagnosis
Using TensorFlow library in Python, we can implement an image recognition skin cancer classifier that tries to distinguish between benign (nevus and seborrheic keratosis) and malignant (melanoma) skin diseases from only photographic 2D RGB images
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ML/AI Image Classifier for Skin Cancer Detection
Skin cancer is one of the most active types of cancer in the present decade. As the skin is the body’s largest organ, the point of considering skin cancer as the most common type of cancer among humans is understandable. It is generally classified into two major categories: nonmelanoma (benign) and melanoma (malignant) skin cancer…
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Webscraping in R – IMDb ETL Showcase
Web scraping in R is an ETL pipeline that perform web data mining by reading HTML tags and converting them to the structured format which can easily be visualized using tidyverse. Let’s scrape movies from IMDb into a data frame in R by invoking the rvest library and then visualize the data frame using ggplot2 and…
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Short-term Stock Market Price Prediction using Deep Learning Models
This blog is about short-term stock market price trend prediction using a comprehensive deep learning LSTM model. Results show that the model achieves overall high accuracy for stock market trend prediction. The following end-to-end sequence provides the detailed Python/Jupyter workflow from data processing to prediction, including the data exploration: 1. Data Preparation Phase #import libraries import…
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ML/AI Regression for Stock Prediction – AAPL Use Case
The following is a set of steps intended for ML/AI regression to predict stock prices. The objective is to simulate available historical stock prices of $AAPL using the SciKit Learn library. 1. Install Yahoo finance library !pip install yfinance 2. Let’s call all dependencies that we will use for this exercise import pandas as pd import…
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Supervised ML/AI Stock Prediction using Keras LSTM Models
(the image was created using Visme [1]). Introduction Stock markets are analyzed either technically or fundamentally [2]. Fundamental analysis studies supply and demand relationships that define the stock price at any given time. Technical analysis uses specialized methods of predicting prices by analyzing past price patterns and levels. There are many techniques used to examine stock…
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Heart Failure Prediction using Supervised ML/AI Technique
Introduction This project is aimed to support ESC guidelines [1] that help health professionals manage people with heart failure (HF) according to the best available evidence. The objective is not only to develop an accurate survival prediction model but also to discover essential factors for the survival prediction of HF patients. The complex nature of HF produces a…
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Supervised ML/AI Breast Cancer Diagnostics (BCD) – The Power of HealthTech
Pilots Related to HealthTech Infographic These plots illustrate the most basic application of ML/AI in BCD as the binary classification problem. Classification usually refers to any kind of problem where a specific type of class label is the result to be predicted from the given input field of data. This is a task which assigns a label value…
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Python Use-Case Supervised ML/AI in Breast Cancer (BC) Classification
https://www.canva.com/design/DAE7oU6O6QQ/share/preview?token=xH-OB2oXeQSrennmqMC2hw&role=EDITOR&utm_content=DAE7oU6O6QQ&utm_campaign=designshare&utm_medium=link&utm_source=sharebutton Acknowledgements with the ML/AI contribution https://hiscidatmlai.blogspot.com/2022/02/digital-transformation-all-way.html… and @VismeApp #Graphics via ref https://visme.co/?ref=al24 Thanks to Mugdha Paithankar [1] and https://kaggle.com/uciml/breast-cancer-wisconsin-data… [2] for the shared open-source content! Introduction Breast Cancer (BC) continues to be the most frequent cancer in females, affecting about one in 8 women and causing the highest number of cancer-related deaths in…
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Real Estate Supervised ML/AI Linear Regression Revisited – USA House Price Prediction
ETL Workflow Linear regression is an algorithm of supervised Machine Learning (ML) in which the predicted output is continuous with having a constant slope [1]. Consider a company of real estate with datasets containing the property prices of a specific region. The price of a property is based on essential factors like bedrooms, areas, and…
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Supervised ML/AI Breast Cancer Diagnostics – The Power of HealthTech
Problem Breast cancer (BC) is the uncontrollable growth of malignant cells in the breasts [1]. BC is the most common cancer with the highest mortality rate. The exact cause of breast cancer is unknown, but some women have a higher risk than others. This includes women with a personal or family history of breast cancer and…
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Supervised Machine Learning Use Case: Prediction of House Prices
This is the application of supervised machine learning to real estate. The goal is to predict sale prices ($) for N selected properties in a state (N>>1000). We are given a csv dataset as a NxM table, where M is the number of property features describing every aspect of the house and surroundings (typically, M<100). …
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