How Much Required Training Data for AI and Machine Learning Algorithms?
Training data is the key input to machine learning (ML), and having the right quality and quantity of data sets is important to get the accurate results. The larger the training data available for ML algorithm, it will help model to perceive the diverse types of objects making easier to recognize when used in real-life predictions.
But the question here is, how will you decide how much of training is enough for your machine learning. As insufficient data will affect your model prediction accuracy while more than enough data can give best results but can you manage the big data or huge quantity of datasets and it also required deep learning or more complex way to fed such data into algorithms.
Actually, there are many factors decide how much training data is required for machine learning like your model complexity, machine learning algorithms and data training or validation process. And in some cases how much data is required to demonstrate that one model is better than another. All these factors considered while choosing the right amount of datasets let we discus more elaborately to find how much data is enough of ML.
Cogito provides training data set for machine learning and AI based applications require a high-quality dataset for developing feasible models.