Tag: machinelearning

  • Overview of AWS Tech Portfolio 2023

    Overview of AWS Tech Portfolio 2023

    This article provides with an overview of 50+ Amazon Web Services (AWS) 2023. AWS is the leading vendor of cloud services and infrastructure, dominating the cloud computing market: Amazon net sales increased by 15% to $127.1 billion in Q3 2022 as compared to $110.8 billion in Q3 2021. AWS segment sales increased by 27% year-over-year to reach…

  • Gold ETF Price Prediction using the Bayesian Ridge Linear Regression

    Gold ETF Price Prediction using the  Bayesian Ridge Linear Regression

    Featured Photo by Pixabay. Let’s set the working directory GOLD import osos.chdir(‘GOLD’) os. getcwd() and import the following libraries from sklearn.linear_model import LinearRegression import pandas as pdimport numpy as np import matplotlib.pyplot as plt%matplotlib inlineplt.style.use(‘seaborn-darkgrid’) import yfinance as yf Let’s read the dataDf = yf.download(‘GLD’, ‘2022-01-01’, ‘2023-03-25’, auto_adjust=True) Df = Df[[‘Close’]] Df = Df.dropna() Let’s…

  • Deep Reinforcement Learning (DRL) on $MO 8.07% DIV USA Stock Data 2022-23

    Deep Reinforcement Learning (DRL) on $MO 8.07% DIV USA Stock Data 2022-23

    MLQ.ai: In fact, many AI experts agree that DRL is likely to be the best path towards AGI, or artificial general intelligence. Spinning Up in DRL at OpenAI: “We believe that deep learning generally—and DRL specifically—will play central roles in the development of powerful AI technology.” Key assumptions and limitations of the DRL framework: Key…

  • SARIMAX X-Validation of EIA Crude Oil Prices Forecast in 2023 – 2. Brent

    SARIMAX X-Validation of EIA Crude Oil Prices Forecast in 2023 – 2. Brent

    Based on our previous study, our today’s focus is on SARIMAX time-series X-validation of the Brent crude oil spot price USD/b: viz. the goal is to verify the following EIA energy forecast in 2023 According to EIA, the Brent spot price will average $83.63/b in 2023. Table of Contents Prerequisites In this study we will be…

  • Testing & Applications of Best AI Content Detector vs Generator APIs for Improved SEO & Social Media Marketing

    Testing & Applications of Best AI Content Detector vs Generator APIs for Improved SEO & Social Media Marketing

    Featured Photo by Tara Winstead on Pexels This is an AI-powered digital marketing project focused on QC testing and relevant business applications of top AI content detectors to be tested against 14 Best Free AI Content Generator & AI Writers For 2023. Table of Contents: 5 AI Content Detector APIs 14 AI Content Generator APIs…

  • SARIMAX X-Validation of EIA Crude Oil Prices Forecast in 2023 – 1. WTI

    SARIMAX X-Validation of EIA Crude Oil Prices Forecast in 2023 – 1. WTI

    Featured Photo by Pixabay Table of Contents: Let’s perform SARIMAX X-validation of EIA WTI and Brent oil prices forecast in the 2nd half of 2023. Recall that SARIMAX (Seasonal Autoregressive Integrated Moving Average with eXogenous factors) is an updated version of the ARIMA model for time series forecasting. SARIMAX is a seasonal equivalent to SARIMA…

  • Comparative ML/AI Performance Analysis of 13 Handwritten Digit Recognition (HDR) Scikit-Learn Algorithms with PCA+HPO

    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…

  • Case Study: Multi-Label Classification of Satellite Images with Fast.AI

    Case Study: Multi-Label Classification of Satellite Images with Fast.AI

    Satellite image classification is the most significant technique used in remote sensing (GIS) for the computerized study and pattern recognition of satellite GIS, which is based on diversity structures of the image that involve rigorous validation of the training samples depending on the used ML/AI classification algorithm. Satellite imagery is important for many applications including…

  • Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing

    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…

  • Interactive Global COVID-19 Data Visualization with Plotly

    Interactive Global COVID-19 Data Visualization with Plotly

    Featured Photo by Artem Podrez on Pexels. Coronavirus Country Profiles: The Value of COVID-19 Data Analytics: Using COVID-19 data to fight and contain the pandemic with data science/analytics and interactive visualization is critical to protect public health and save lives. Using global data through mobile & web applications will allow us to beat COVID-19 faster.…

  • AI-Based ECG Recognition – EOY ’22 Status

    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.…

  • Top 8 Free AI APIs for Content Design 2023

    Top 8 Free AI APIs for Content Design 2023

    Featured Photo by Tara Winstead on Pexels Photo Restoration GFPGAN can be used to restore your old photos or improve AI-generated faces.To use it, simply upload your image. Recommend the Github Repo The results are very impressive and work well even with very low-quality images. CopyWriter AIs Copy.ai for emails, blogs, and social media – experience the full power…

  • 99% Accurate Breast Cancer Classification using Neural Networks in TensorFlow 2.11.0

    99% Accurate Breast Cancer Classification using Neural Networks in TensorFlow 2.11.0

    Workflow The entire workflow is as follows: Prerequisites We need to install the following libraries: !pip install –user tensorflow BC Dataset In this study, we use the BC Wisconsin (Diagnostic) Dataset to predict whether the BC is benign or malignant. Model features are computed from a digitized image of a fine needle aspirate (FNA) of…

  • The Power of AIHealth: Comparison of 12 ML Breast Cancer Classification Models

    The Power of AIHealth: Comparison of 12 ML Breast Cancer Classification Models

    Contents: BC Dataset Conventionally, the Breast Cancer Wisconsin (Diagnostic) Data Set has been used to predict whether the breast cancer is benign or malignant. Features were computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. The dataset can…

  • Textual Genres Analysis using the Carloto’s NLP Algorithm

    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…

  • A Roadmap from Data Science to BI via ML

    A Roadmap from Data Science to BI via ML

    This post describes a Data Science (DS) roadmap, with relevant business applications. It has been written for aspiring data scientists, technical experts who work with data scientists, data-driven technology stakeholders, or anyone interested in learning about what DS is and what it’s used for. Why DS: The average base salary of a data scientist in…

  • A Comparison of Scikit Learn Algorithms for Breast Cancer Classification – 2. Cross Validation vs Performance

    A Comparison of Scikit Learn Algorithms for Breast Cancer Classification – 2. Cross Validation vs Performance

    Featured Photo by Tara Winstead @ Pexels. This post is a continuation of the previous breast cancer (BC) study focused on a comparison of available Scikit-Learn binary classifiers (Logistic Regression, GaussianNB, SVC, KNN, Random Forest, Extra Trees, and Gradient Boosting) in terms of cross validation and model performance/scalability scores. Contents: Let’s set the working directory YOURPATH…

  • 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 goal of this post is a comparison of available binary classifiers in Scikit-Learn on the breast cancer (BC) dataset. The BC dataset comes with the Scikit-Learn package itself. Contents: Data Analysis Let’s set the working directory YOURPATH import osos.chdir(‘YOURPATH’) os. getcwd() and load the BC dataset from sklearn import datasetsdata = datasets.load_breast_cancer() with the…

  • Build A Simple NLP/NLTK Chatbot

    Build A Simple NLP/NLTK Chatbot

    Featured Image – Canva. How Can Chatbots Help Improve Your Bottom-line?  A chatbot is a computer program or software that automates conversation with a user. They can be programmed with different responses based on what a user chooses or requests. Chatbots can provide real-time customer support and are therefore a valuable asset in many industries.  Contents: You can build an industry-specific…

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

    DL-Assisted ECG/EKG Anomaly Detection using LSTM Autoencoder

    Featured Photo by Luan Rezende Automatic detection and alarm of abnormal electrocardiogram (ECG aka EKG) events play an important role in an ECG monitor system; however, popular classification models based on standard supervised ML fail to detect abnormal ECG accurately. In this project, we implement an ECG anomaly detection framework based on the recently proposed…