Fine tuning machine learning predictive model is a crucial step to improve accuracy of the forecasted results. In the recent past, I have written a number of articles that explain how machine learning works and how to enrich and decompose the feature set to improve accuracy of your machine lear...
Edit: Regarding 'accuracy' in the last line of the log, that is the accuracy of the network after all epochs run against the test data set. This is usually more closer to 'val_acc' than accuracy (like in the case above it is 79). This just means that the samples in test data ali...
For example, with photograph image data, you can get big gains by randomly shifting and rotating existing images. It improves the generalization of the model to such transforms in the data if they are to be expected in new data. This is also related to adding noise, what we used to call...
The first example gave a validation accuracy > 75% and the second one gave an accuracy of < 65% and if you compare the losses for epochs below 100, its less than < 0.5 for the first one and the second one was > 0.6. But how is the second case better?. The second one to me ...
thresholds. The second is to set default rules to trigger system preset rule events, such as machine restart. At the same time, the operation and maintenance team often does not rely on a single monitoring tool, and often needs to set corresponding monitoring alarms in various tools at ...
Testing is an essential aspect of the development of any software system, including Machine Learning (ML) systems. ML models are designed to learn from data and improve their performance over time, which makes them powerful tools for solving complex problems in a wide range of applications. Howev...
When voice or speech recognition accuracy is flawed, the errors can be glaring, and occasionally entertaining. Read more.
“Instead, Lambda and its serverless capacity help us answer those questions in milliseconds, and helps us achieve decision accuracy upwards of 99.9%. It’s hugely efficient and cost-effective technology for us and our clients.” Fraud.net also uses Amazon Kinesis to process...
For data scientists, continual learning will ultimately optimize models for accuracy, improve model performance, and save retraining time by making models auto-adaptive. Machine learning pipeline with continual learning Machine learning pipeline The diagram above illustrate...
How to improve fairness In machine learning and AI,fairnessrefers to models that arefree from algorithmic biases in their design and training. A fair machine learning model is one that's trained to make unbiased decisions. Before identifying how to improve fairness, it's important to understand ...