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Tensorflow in deep learning is an open end-to-end machine learning platform. It's a symbolic math toolkit that integrates data flow.
Learn the basics of CNN (Convolutional Neural Networks), including layers, padding, pooling, ReLU, & Python implementation in this guide.
In this article, let us work on creating a angle detection model using computer vision in python and see its real world applications
In this article, we will be making hand landmarks detection model with the profound library i.e. mediapipe as the base library
Explore the significance of Object Detection, how it functions, training data essentials, Bounding Box Evaluation using IOU.
Explore the Convolutional Neural Networks in deep learning, covering architecture, layers, training, limitations, and Python implementation.
In this article, we will see how to Lenskit build a recommender system and evaluate different recommender algorithms using the nDCG metric.
Graph Neural Networks (GNNs), their types, working, applications, and use cases. Learn how GNNs compare to CNNs for graph-based data analysis. Read Now!
In this article, lets understand the Carbon Footprint of AI and Deep Learning and what this computational task is costing us
The Naive Bayes algorithm is a straightforward and quick machine learning algorithm that is frequently used for real-time predictions.
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