AI MaverickUnderstanding Random Fourier Features for Kernel Approximation*This article aims to simplify [1] for easier understanding. All credit for the original content goes to its respective authors [1].Apr 21Apr 21
AI MaverickReinforcement LearningReinforcement learning or RL is a type of machine learning where an agent learns to behave in an environment by trial and error. The agent…Aug 24, 2023Aug 24, 2023
AI MaverickAll about loss functions in machine learningIn machine learning, a loss function is a mathematical function that measures how well a machine learning model is able to make…Feb 16, 2023Feb 16, 2023
AI MaverickEvaluate the Decision Regressor TreeHow to Evaluate the decision Regressor Tree Performance with the terminal region?Jun 10, 2023Jun 10, 2023
AI MaverickAll about Long Short-Term MemoryAll about Long Short-Term Memory or LSTM in Machine learningMay 18, 2023May 18, 2023
AI MaverickHow to measure classifier performanceClassification is a type of supervised machine learning problem where the goal is to predict the class or category of an input instance…May 6, 2023May 6, 2023
AI MaverickData segmentation in computer visionData segmentation in computer vision refers to the process of dividing an image or video dataset into smaller, more manageable subsets…Mar 30, 2023Mar 30, 2023
AI MaverickLight Gradient Boosting MachineLight GBM (Light Gradient Boosting Machine) is a popular open-source framework for gradient boosting. It is designed to handle large-scale…Mar 25, 2023Mar 25, 2023
AI Maverickleave-out Vs KFoldIn machine learning, a “splitter” refers to a tool or technique that is used to split a dataset into separate subsets for training and…Mar 21, 2023Mar 21, 2023
AI MaverickSplitters in Machine learningIn machine learning, a splitter is a function or module used to split a dataset into two or more subsets for different purposes. Splitting…Mar 21, 2023Mar 21, 2023
AI MaverickMultitask learning (MTL)Multitask learning (MTL) is a machine learning approach that involves training a model to perform multiple tasks simultaneously using the…Mar 7, 2023Mar 7, 2023
AI MaverickIntroducing Rock-Paper- Scissors DatasetAn image dataset is a collection of digital images that are organized and labeled for use in machine learning and computer vision tasks…Feb 11, 2023Feb 11, 2023
AI MaverickImage datasets for developing ML algorithmsIntroducing well-known Image datasets for developing machine learning algorithmsFeb 7, 2023Feb 7, 2023
AI MaverickHow to enhance training speed in TensorFlowTensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math…Feb 7, 20231Feb 7, 20231
AI MaverickBatch Normalization in deep learningBatch Normalization is a technique in deep learning used to normalize the inputs of each layer in a network, in order to reduce internal…Feb 5, 2023Feb 5, 2023
AI MaverickSchedule learning rate in deep-learningSchedule learning rate refers to the method of gradually decreasing the learning rate over time during the training of a deep learning…Feb 4, 2023Feb 4, 2023
