Tag: images
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Hugging Face NLP, Streamlit, PyGWalker, TF & Gradio App
Table of Contents Streamlit/Dash/Jupyter PyGWalker EDA Demo PyGWalker and Dash — Creating a Data Visualization Dashboard In Less Than 20 Lines of Code PyGWalker Test PyGWalker Tutorial: A Tableau-Like Python Library for Interactive Data Exploration and Visualization PyGWalker: A Python Library for Visualizing Pandas Dataframes You’ll Never Walk Alone: Use Pygwalker to Visualize Data in…
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Image Based Fast Forest Fire Detection with TensorFlow
A recent study showcases the use of artificial intelligence (AI) and deep learning (DL) for efficient wildfire prediction and management. Utilizing a fast DL approach based on the TensorFlow Convolution Neural Network (CNN) algorithm, researchers trained models to distinguish between fire and non-fire images using a public-domain dataset. The implemented system predicted fires accurately and…
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Effective 2D Image Compression with K-means Clustering
The post explores the application of the K-means clustering algorithm, a popular unsupervised Machine Learning algorithm, for image compression. By segmenting 2D images into different clusters, the algorithm effectively reduces storage space without compromising on image quality or resolution. It also demonstrates the application of this approach through a case study, where optimal results were…
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About Face Recognition ML Algorithms
Facial Recognition (FR) involves mapping an individual’s facial features mathematically and storing the data as a faceprint. This case study outlines the process of Exploratory Data Analysis (EDA) and performance QC analysis for ML/AI workflows using public-domain datasets and real-time webcam GUI. The study includes the use of SVM for FR, dataset splitting, ML model…
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AI-Driven Object Detection & Segmentation with Meta Detectron2 Deep Learning
The post introduces Detectron2, a powerful object detection and image recognition platform developed by Facebook AI Research (FAIR). It discusses the platform’s applications in computer vision research and production, as well as its capabilities such as panoptic segmentation and Densepose. The post also covers aspects of using Detectron2, including installation, model training, and inference, and…
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Turkey/Syria Earthquake Live Knowledge Update & Charity Guide
Turkey has recently experienced a high frequency of earthquakes, the largest being a magnitude of 7.8 near Nurdağı, Gaziantep, on February 6th, 2023. This was one of the most powerful earthquakes in the country’s history, resulting in over 22,000 deaths and significant damage across Southern Turkey and Northern Syria. The aftermath left many survivors homeless,…
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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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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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AI-Guided Drug Recommendation
AI-Guided Drug Recommendation in Python using NLP text processing. Key steps: WordCount images, NLP Pre-Processing, NER via spacy, LDA topic modelling, and Word2Vec Vectorization for reviews using pretrained glove model. Input data: the Kaggle UCI ML Drug Review dataset. Applications in the pharmaceutical industry, including drug R&D, drug repurposing, improving pharmaceutical productivity, and clinical trials,…
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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…
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