TensorFlow

In recent years, there has been a significant surge in the adoption of artificial intelligence (AI) and machine learning (ML) technologies across a wide range of industries. Frameworks such as TensorFlow, PyTorch, and Scikit-learn have emerged as popular choices for AI development due to their versatility and robustness. However, the seamless integration of AI into enterprise-grade, production-ready applications poses unique challenges that need to be addressed. Spring, a widely recognized enterprise-level framework, is celebrated for its exceptional robustness, scalability, and…

Here is a basic tutorial on setting up and training image generation models using Generative Adversarial Networks (GANs) with TensorFlow and PyTorch. This guide assumes a fundamental understanding of Python and basic machine learning concepts. 1. Setting up Your Environment Install Necessary Libraries Ensure you have Python installed. You will also need to install TensorFlow or PyTorch along with some other essential libraries. For TensorFlow: Shell   pip install tensorflow numpy matplotlib For PyTorch: Shell   pip install torch torchvision…

For container applications, it’s hard to find problems resulting from memory overuse. In case usage goes beyond container memory limit, an application can silently fail without leaving any trace. In this article, I’ll go through some of the techniques that can be used to identify the source of memory consumption in a Java container application. Memory Type In a typical Java application, memory can be broadly divided into heap and non-heap. Heap memory can be set by providing relevant JVM…

In the ever-evolving world of artificial intelligence, developers are often confused when choosing the right deep learning framework. Whether it’s TensorFlow’s extensive documentation, backed by the power of the Google Brain Team, or PyTorch’s dynamic computational graph, courtesy of Facebook’s AI Research lab, the choice is seldom straightforward. Some frameworks shine in semantic segmentation, while others are GPU benchmark tests. An expedition will take us through the complexities of TensorFlow, PyTorch, Keras, Caffe, and the Microsoft cognitive toolkit. We’ll explore…

In an age where artificial intelligence (AI) is no longer a futuristic concept but a present reality, its integration into the software development process has become increasingly significant. As a senior software engineer deeply embedded in the world of AI, I’ve witnessed firsthand the transformative impact of AI tools and frameworks in optimizing and enhancing software development. This blog aims to delve into the key AI tools and frameworks that are not just beneficial but essential for today’s software engineers.…

In today’s digital age, the proliferation of Deepfake technology and voice phishing (vishing) tactics presents a significant challenge to the authenticity and security of digital communications. Deepfakes manipulate audio and video to create convincing counterfeit content, while vishing exploits voice simulation to deceive individuals into revealing sensitive information. The need to accurately identify and mitigate these threats is paramount for protecting individuals and organizations from the potential consequences of misinformation, fraud, and identity theft. Understanding Deepfakes and Vishing Deepfakes are…

An open-source software library for artificial intelligence and machine learning is called TensorFlow. Although it can be applied to many tasks, deep neural network training and inference are given special attention. Google Brain, the company’s artificial intelligence research division, created TensorFlow. Since its initial release in 2015, it has grown to rank among the most widely used machine learning libraries worldwide. Python, C++, and Java are just a few of the programming languages that TensorFlow is accessible. Additionally, it works…

This article is an excerpt from my book TinyML Cookbook, Second Edition. You can find the code used in the article here. Getting Ready The application we will design in this article aims to continuously record a 1-second audio clip and run the model inference, as illustrated in the following image: Figure 1: Recording and processing tasks running sequentially From the task execution timeline shown in the preceding image, you can observe that the feature extraction and model inference are…

The calculation of the norm of vectors is essential in both artificial intelligence and quantum computing for tasks such as feature scaling, regularization, distance metrics, convergence criteria, representing quantum states, ensuring unitarity of operations, error correction, and designing quantum algorithms and circuits. You will learn how to calculate the Euclidean (norm/distance), also known as the L2 norm, of a single-dimensional (1D) tensor in Python libraries like NumPy, SciPy, Scikit-Learn, TensorFlow, and PyTorch.  Understand Norm vs Distance Before we begin, let’s…