Tag: Python

  • 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…

  • ML/AI GHG Monitoring and Forecast

    The graphs show monthly mean carbon dioxide measured at Mauna Loa Observatory, Hawaii. We extract some insights about the historical data and its statistical properties using the scikit-learn ML/AI Python library. We discovered that atmospheric CO2 concentration is expected to increase in future, highlighting the fact that emissions must be reduced, to ensure the prosperity…

  • Diabetes Prediction using ML/AI in Python

    The post focuses on developing a machine-learning model to predict diabetes using patient diagnostic data from the UCI Machine Learning Repository, featuring blood tests and obesity metrics. Implemented classifiers include a random forest, decision tree, XGBoost, and an SVM. The model is trained on this data, achieving highest accuracy with the random forest method (approx.…

  • E-Commerce Cohort Analysis in Python

    Cohort analysis (CA) is a beneficial tool in e-commerce marketing to monitor campaign health, particularly in customer retention rates. By grouping customers into cohorts, marketers can assess the effectiveness of their efforts, track customer behaviors, and identify the most valuable demographic segments. The article exemplifies how CA can be applied to customer transaction data using…

  • 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…

  • HealthTech ML/AI Use-Cases

    About Supervised ML/AI Breast Cancer Diagnostics Python Use-Case Supervised ML/AI in Breast Cancer (BC) Classification Heart Failure Prediction using Supervised ML/AI Technique Diabetes Prediction using ML/AI in Python

  • E-Commerce Data Science Use-Case

    In response to the surge of online shopping, a Data Science (DS) based customer analytics platform focusing on customer profiling, sentiment analysis, and customer lifetime value prediction is being developed. This platform utilizes the Exploratory Data Analysis (EDA) pipeline employing the Python library, Pandas. The platform is capable of product recommendation, customer trend analysis, sales…

  • E-Commerce ML/AI Classification

    The article outlines the process of using TensorFlow to categorize clothing images. It involves pre-processing data, building an ML model, and making predictions. The application relies on Python and Jupyter Anaconda IDE, using the tf.keras high-level API. The dataset comprises 60,000 grayscale images in various fashion categories, with data divided into training and testing sets…

  • Heart Failure Prediction using Supervised ML/AI Technique

    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 significant amount…

  • 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…

  • 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…

  • 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…