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#deep-learning
Welcome to the DataSavantMaven blog, where the fusion of data engineering, machine learning, and data science opens the road for ground-breaking discoveries. I am eager to offer my knowledge and thoug…
Introduction Deep learning has revolutionized the field of artificial intelligence, enabling remarkable advancements across various domains. Julia, a high-performance programming language, has emerged…
Introduction Most models used in modern-day computer vision tasks like object detection, generative computer vision, object recognition, and so on all have their backbone architecture in convolutional…
Augmented Reality (AR) has opened up exciting possibilities for creating immersive digital experiences that seamlessly integrate with the real world, and NLP(Natural Language Processing) has proved to…
Generative Adversarial Network (GAN), a type of machine learning algorithm, was introduced in 1962 in chatbots. By 2014, generative AI applications were able to create authentic images, videos, audio …
Great!! You have made it to the final part of the series. In this part, we will train our model and test it by building a prediction function. Luckily, there is no math involved in this part 😃. So le…
After Forward Propagation we need to define a loss function to calculate how wrong our model is at this moment. For a simple binary classification problem, the loss function is given below. $$Cost:J_{…
Step1: Import Necessary Libraries Numpy: Numpy arrays are very fast and can perform large computations in a very short time. Matplotlib: Used for Visualizations. Tensorflow: This is an open-source lib…
Deep learning is a branch of machine learning and artificial intelligence that uses advanced computations to model the structure and operation of the neural networks in the human brain. In order to automatically extract and learn complicate…
Hey readers, I’m Shiwanshi, and this is my first blog on Hashnode. Being an Artificial Intelligence student, I was so happy when I learned about Generative Adversarial Networks (GANs) long before it …
