Machine Learning (ML) Pointwise Convolution In this article, we will cover Pointwise Convolution which is used in models like MobileNetV1 and compared it with other variants like Depthwise Convolution and Depthwise Seperable Convolution.
Machine Learning (ML) RNN Based Encoder and Decoder for Image Compression In this article, we will be discussing a about RNN Based Encoder and Decoder for Image Compression.
Machine Learning (ML) Image compression using K means clustering In this article, we will look at Image Compression using K-means Clustering which is an unsupervised learning algorithm. This is a lossy Image Compression technique.
Machine Learning (ML) Image Compression: ML Techniques and Applications In this article, we will discuss Image Compression application in depth involving Machine Learning Techniques like RNN based Encoder and Decoder and applications of Image Compression.
Machine Learning (ML) Gaussian Error Linear Unit (GELU) In this article, we will talk about a relatively new activation function and somewhat better as well. Basically we will be discussing about Gaussian Error Linear Unit or GeLU.
Machine Learning (ML) kn2row / kn2col Convolution In this article, we will cover 2 different convolution methods: Kn2row and Kn2col Convolution which are alternatives to Im2row and Im2col. Kn2row and Kn2col are space efficient variants.
Machine Learning (ML) Im2row Convolution In this article, we will understand about Im2row Convolution which is an approach to perform Convolution by modifying the layout of image and filter. It is a better alternative to Im2col.
Machine Learning (ML) Filter and Channel Pruning In this article, we will cover the idea of Pruning which is an important optimization technique for CNN models. It reduces the size of models as well as the Inference time. We dive into two main types of Pruning that is Channel Pruning and Filter Pruning.
Machine Learning (ML) Different types of CNN models In this article, we will discover various CNN (Convolutional Neural Network) models, it's architecture as well as its uses. Go through the list of CNN models.
Machine Learning (ML) Squeeze and Excitation (SE) Network This article describes what are Convolutional Neural Network and What are Squeeze and Excitation blocks.
Machine Learning (ML) Sigmoid Activation (logistic) in Neural Networks In this article, we will understand What are Sigmoid Activation Functions? And What are it’s Advantages and Disadvantages?
Machine Learning (ML) Dying ReLU Problem In this article, we will understand What is ReLU? and What do we mean by “Dying ReLU Problem” and what causes it along with measures to solve the problem.
Machine Learning (ML) Types of Dimensionality Reduction Techniques In this article, we will learn Why is Dimensionality Reduction important and 5 different Types of Dimensionality Reduction Techniques like Principal Component Analysis, Missing Value Ratio, Random Forest, Backward Elimination and Forward Selection.