Chic perennial Intelligence

  • Squeeze-and-Excitation: Enhancing CNNs for Improved Feature Representation

    Squeeze-and-Excitation: Enhancing CNNs for Improved Feature Representation

    An Attention Mechanism for Channel-Wise Feature Enhancement Introduction Squeeze-and-Excitation (SE) Networks are a type of artificial neural network that helps computers better understand and recognize images. They do this by focusing on the important parts of an image and ignoring the unimportant parts. The SE module in the network is made up of two main…

  • Unleashing the Full Potential of Deep Learning Models: A Guide to Quantization Techniques

    Unleashing the Full Potential of Deep Learning Models: A Guide to Quantization Techniques

    Photo by Lucas Pezeta Precision at a fraction of the size: Experience the power of quantization for your deep learning models Introduction Model quantization is a technique for reducing the precision of the weights and activations of a neural network model. This process can be used to decrease the model’s memory footprint and computational complexity,…

  • ChatGPT: The Future of Google search.

    ChatGPT: The Future of Google search.

    How OpenAI’s chatGPT beats google search engine, in terms of results more insightful and catchy without any loitering. A revolutionary AI that has handed a ladder to the existing AI to climb wonders. (November 30, 2022) ChatGPT was built on top of GPT-3, their last flagship transformers-based model. Its response framing and text articulation have…

  • Shout out to GAN (Start ver.)

    Shout out to GAN (Start ver.)

    Writing after a long time, Here’s the basic + in-depth mix explanation of Generative adversarial networks and Style-Based Generative Adversarial networks. Introduction GAN is simply a generative model that generates new data from the input data. They are used to perform unsupervised operations. They work majorly with image data and also audio data. The Generative…

  • Are you eligible for data science?

    Are you eligible for data science?

    Here is all you need to hit on data science, machine learning, etc in a flawless manner. Starting might sense difficult, but if directed properly, it may lead to wonders. The same happens with people who start learning data science and machine learning. People just directly dive into the actual machine learning code and try…