Sanjay DuttaHow to Calculate Precision, Recall, F1, Confusion Matrix, ROC AUC for Deep Learning ModelsEvaluating the performance of deep learning models is crucial in determining how well a model has learned to make predictions. Common…Jul 30Jul 30
Sanjay DuttaWhat is Data Bias in Machine Learning?When we talk about bias in the context of machine learning and data preprocessing, we refer to the potential for certain patterns or…Jul 16Jul 16
Sanjay DuttaWhat is Shuffling the Data? A Guide for StudentsWhen working with datasets in machine learning, one crucial preprocessing step is shuffling the data. Shuffling is the process of randomly…Jul 16Jul 16
Sanjay DuttaUnderstanding Chaining Transformations in Data Preprocessing: A Guide for StudentsWhen working with data, especially in machine learning, it’s crucial to preprocess the data to ensure it is in the right format and…Jul 16Jul 16
Sanjay DuttaUnderstanding Batch Normalization:Training deep neural networks can be challenging due to issues like internal covariate shift, where the distribution of inputs to each…Jul 15Jul 15
Sanjay DuttaUnderstanding Glorot and He Initialization: A Guide for StudentsWhen training deep neural networks, the initialization of the weights can significantly affect how well and how quickly the model learns…Jun 9Jun 9
Sanjay DuttaUnderstanding Vanishing and Exploding GradientsWhen you’re diving into the world of neural networks, you’ll often hear about the vanishing and exploding gradients problems. These issues…Jun 7Jun 7
Sanjay DuttaMastering Hyperparameters: Learning Rate, Batch Size, and MoreWhen designing and training neural networks, tuning hyperparameters is crucial for achieving optimal performance. Beyond the number of…Jun 5Jun 5
Sanjay DuttaNumber of Neurons per Hidden Layer in Neural Networks: A GuideWhen designing neural networks, one of the critical decisions you’ll face is determining the number of neurons in each hidden layer. While…Jun 5Jun 5