Mlearning.ai

NOVEMBER 23, 2023

This Only Applies to Supervised Learning Introduction If you’re like me then you probably like a more intuitive way of doing things. When it comes to machine learning, we often have that one (or two or three) “go-to” model(s) that we tend to rely on for most problems. With Lazypredict. Call-To-Action Enjoyed this blog post?

Supervised Learning 52

Supervised Learning Cross Validation EDA Machine Learning 52

Mlearning.ai

SEPTEMBER 24, 2023

Figure 1: Brute Force Search It is a cross-validation technique. This is a technique for evaluating Machine Learning models. Figure 2: K-fold Cross Validation On the one hand, it is quite simple. Running a cross-validation model of k = 10 requires you to run 10 separate models. Packt Publishing.

Cross Validation 52

Cross Validation Algorithm Supervised Learning Python 52

Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Mlearning.ai

MARCH 7, 2023

The goal of ML is to discover patterns and not simply memorize our training data, the fundamental problem is how to discover that pattern that generalizes. In real-life ML work, we fit models using a finite collection of data even with the most extreme scale, the number of available data points remains small.

Deep Learning 52

Deep Learning Deep Learning Cross Validation ML 52

Heartbeat

AUGUST 29, 2023

Here are a few deep learning classifications that are widely used: Based on Neural Network Architecture: Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) Autoencoders Generative Adversarial Networks (GAN) 2. Semi-Supervised Learning : Training is done using both labeled and unlabeled data.

Deep Learning 52

Deep Learning Deep Learning Cross Validation Data Quality 52

The MLOps Blog

APRIL 20, 2023

Annotation and labeling: accurate annotations and labels are essential for supervised learning. Hardware-specific optimization : optimize your model for the specific hardware it will be deployed on, such as using libraries like TensorFlow Lite or Core ML, which are designed for edge devices like smartphones and IoT devices.

ML 64

ML ML Cross Validation Data Quality 64

Mlearning.ai

JANUARY 31, 2023

The test runs a 5-fold cross-validation. On the other hand, the labels put by me only rely on time, but in practice we know that’s gonna make errors, so a classifier would learn from bad data. Machine learning would be a lot easier otherwise. As you can see, using hand-made labels, the SVM performs quite well.

Clustering 52

Clustering Algorithm Machine Learning Machine Learning 52