Tag: machinelearning
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Dealing with Imbalanced Data in HealthTech ML/AI – 1. Stroke Prediction
This post discusses the prediction of stroke using machine learning (ML) models, focusing on the use of early warning systems and data balancing techniques to manage the highly imbalanced stroke data. It includes a detailed exploration of the torch artificial neural network training and performance evaluation, as well as the implementation and evaluation of various…
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Dabl Auto EDA-ML
Dabl, short for Data Analysis Baseline Library, is a high-level data exploration library in Python that automates repetitive data wrangling tasks in the early stages of supervised machine learning model development. Developed by Andreas Mueller and the scikit-learn community, it facilitates data preprocessing, advanced integrated visualization, exploratory data analysis (EDA), and ML model development, demonstrated…
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Using AI/ANN AUC>90% for Early Diagnosis of Cardiovascular Disease (CVD)
The project utilizes AI-driven cardiovascular medicine with a focus on early diagnosis of heart disease using Artificial Neural Networks (ANN). Aiming to improve early detection of heart issues, the project processed a dataset of 303 patients using Python libraries and conducted extensive exploratory data analysis. A Sequential ANN model was subsequently built, revealing excellent performance…
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Overview of AWS Tech Portfolio 2023
This summary focuses on the extensive capabilities of Amazon Web Services (AWS) by 2023, highlighting its 27% year-on-year growth and a net sales increase to $127.1 billion. AWS emerges as the top cloud service provider, offering over 200 services including compute, storage, databases, networking, AI, and machine learning. It is constantly expanding operations, having opened…
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Gold Price Linear Regression
This content focuses on predicting gold prices using machine learning algorithms in Python. With an 80% R2-score and a Sharpe ratio of 2.33, it suggests a potential 8% revenue from an investment starting in December 2022. The forecasted next-day price for SPDR Gold Trust Shares is $185.136, aligning with Barchart’s “100% BUY” signal.
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Deep Reinforcement Learning (DRL) on $MO 8.07% DIV USA Stock Data 2022-23
This study applies the Deep Reinforcement Learning (DRL) algorithm to USA stocks with +4% DIV in 2022-23, focusing on Altria Group, Inc. The study addresses accurate stock price predictions and the challenges in traditional methods. Recent advances in DRL have shown improved accuracy in stock forecasting, making it suitable for turbulent markets and investment decision-making.
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SARIMAX Crude Oil Prices Forecast – 2. Brent
This study focuses on validating the EIA energy forecast for the 2023 Brent crude oil spot price using SARIMAX time-series cross-validation. It includes prerequisites, data loading, ETS decomposition, ADF test, SARIMAX modeling, predictions, model evaluation, and summary. The predictions align with the EIA forecast, with discrepancies within predicted confidence intervals.
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Testing & Applications of Best AI Content Detector vs Generator APIs
This is an AI-powered digital marketing project that tests and discusses applications of top AI content detectors and generators. It reviewed 14 AI content generator and 5 AI detector APIs for 2023 and tested for results. It additionally explored utilizing AI to improve SEO performance, including competitor analysis, discovery of high-potential keywords and topics, and…
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SARIMAX Crude Oil Prices Forecast – 1. WTI
The content discusses a detailed forecast of Brent and WTI oil prices for 2023, using Python, SARIMAX and Time Series Analysis. The data indicates volatility in the oil market starting 2023, with prices set to decrease from 2022 levels. Experts also warn of a potential US recession in 2023, which could further impact the oil…
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Comparative ML/AI Performance Analysis of 13 Handwritten Digit Recognition (HDR) Scikit-Learn Algorithms with PCA+HPO
Featured Photo by Torsten Dettlaff on Pexels The article consists of the following three parts: 3. Unsupervised ML using the Principal Component Analysis (PCA) for the dimensionality reduction within Parts 1 and 2. Our main goal is to build a text and graphics report comparing the main scikit-learn classification metrics: accuracy_score, classification_report (precision, recall, and…
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Case Study: Multi-Label Classification of Satellite Images with Fast.AI
The post discusses the use of satellite image classification in remote sensing to identify objects such as buildings, woodlands, and water areas. It highlights the application of a machine learning technique using Fast.ai on the Planet dataset, which comprises satellite images of diverse scenes. The method involves training a model with pre-selected classes for accurate…
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Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing
Machine learning and deep learning are invaluable in optimizing supply chain operations in fashion retail. Even smaller retailers are leveraging ML algorithms to meet customer demands. Neural network models, particularly Convolution Neural Networks (CNN) are used to classify clothing images, like the Fashion-MNIST dataset, with high accuracy. Hyperparameter optimization using GridSearchCV and Nadam optimizer are…
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Interactive Global COVID-19 Data Visualization with Plotly
COVID-19, caused by SARS-CoV-2 virus, has affected 227.2 million people and caused 4,672,629 deaths. The disease, first reported in Wuhan, has spread globally. Data visualization tools like Plotly and analysis of Kaggle datasets provide insights into the pandemic’s impact, with the US leading in confirmed cases and deaths. China has managed to control the spread.
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AI-Based ECG Recognition – EOY ’22 Status
Featured Photo by cottonbro studio on pexels. Electrocardiography (ECG) is the method most often used to diagnose cardiovascular diseases. The recent study demonstrates that an AI is capable of automatically diagnosing the abnormalities indicated by an ECG. In this post we will review and illustrate how AI applies to ECG analysis to outperform traditional ECG analysis.…
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Top 8 Free AI APIs for Content Design 2023
The post features a variety of AI-powered tools for content creation, including photo restoration, copywriting, and content generation. It showcases various AI systems such as GFPGAN for photo improvement, Copy.ai for copywriting, Notion.ai for generating insights, and Lumen5 for video creation. Lalal.ai is highlighted for audio stem splitting. Additionally, it offers links to explore more…
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99% Accurate Breast Cancer Classification using Neural Networks in TensorFlow
Breast cancer is a significant global health concern, affecting 12% of women. Machine Learning and Artificial Intelligence techniques play a crucial role in early diagnosis using image features. The study demonstrates a successful Neural Network model for breast cancer classification, achieving 98% accuracy and 98% F1-score. Multiple metrics confirm the model’s efficiency.
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The Power of AIHealth: Comparison of 12 ML Breast Cancer Classification Models
AI Health is leveraging Machine Learning (ML) and Artificial Intelligence (AI) for early diagnosis and prediction of breast cancer (BC), utilizing different ML techniques for binary classification of the disease. A comparative analysis demonstrated that Linear Regression was the most effective classifier based on various performance metrics. This research aims to integrate ML in public…
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Textual Genres Analysis using the Carloto’s NLP Algorithm
Featured Photo by Dominika Roseclay on Pexels. Computational Linguistics (CL) is the scientific study of language. Oftentime, CL is linked to the Python software development based on Natural Language Processing (NLP) libraries. NLP basically consists of combining machine learning (ML) techniques with text, and using math and statistics to get that text in a format…
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A Roadmap from Data Science to BI via ML
The blog post presents a comprehensive roadmap to Data Science (DS), providing an overview of career prospects, the field’s intersections with Mathematics, Statistics, and Computer Science, and its business relevance. The text details the earning potential of data scientists and the steps towards becoming one, including Data Analysis, Machine Learning, and Business Intelligence. It highlights…
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A Comparison of Scikit Learn Algorithms for Breast Cancer Classification – 2. Cross Validation vs Performance
The post is a continuation of a previous breast cancer study comparing Scikit-Learn binary classifiers for cross validation and model performance. The classifiers compared include Logistic Regression, GaussianNB, SVC, KNN, Random Forest, Extra Trees, and Gradient Boosting. Learning curves show the comparison of classifier performance. Results indicate GaussianNB is more efficient than SVC in terms…
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