Data Preparation Challenges in Machine Learning
Machine learning initiatives can be very difficult. The quality and quantity of data that needs to be processed, the complexity of the underlying algorithms, and the requirement for accuracy and dependability can all contribute to their difficulty. Additionally, the development and implementation of machine learning applications can be costly and time-consuming. Despite the fact that […]
Gradient Descent
The gradient descent technique is a popular optimization method (to find minimum error) in deep learning and machine learning. Gradient descent modifies the parameters in order to minimize specific functions. Backward propagation technique is used in deep learning whereas weights and biases are optimized in linear regression. A gradient calculates how much a function’s output […]