Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 26, 2023

Unstable Support Vector Machines (SVM) Support Vector Machines can be prone to high variance if the kernel used is too complex or if the cost parameter is not properly tuned. Regular cross-validation and model evaluation are essential to maintain this equilibrium.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Decision Trees 52

Mlearning.ai

FEBRUARY 15, 2023

Deep learning models with multilayer processing architecture are now outperforming shallow or standard classification models in terms of performance [5]. Deep ensemble learning models utilise the benefits of both deep learning and ensemble learning to produce a model with improved generalisation performance.

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

Heartbeat

OCTOBER 23, 2023

By analyzing historical data and utilizing predictive machine learning algorithms like BERT, ARIMA, Markov Chain Analysis, Principal Component Analysis, and Support Vector Machine, they can assess the likelihood of adverse events, such as hospital readmissions, and stratify patients based on risk profiles.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Mlearning.ai

MAY 23, 2023

Another example can be the algorithm of a support vector machine. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. What is deep learning?

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

Heartbeat

JUNE 14, 2023

Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks. Support vector machine classifiers as applied to AVIRIS data.” Measuring Calibration in Deep Learning. We’re committed to supporting and inspiring developers and engineers from all walks of life.

Deep Learning 59

Deep Learning Deep Learning Support Vector Machines Cross Validation 59

DagsHub

APRIL 21, 2024

Moving the machine learning models to production is tough, especially the larger deep learning models as it involves a lot of processes starting from data ingestion to deployment and monitoring. It provides different features for building as well as deploying various deep learning-based solutions.

Machine Learning 59

Machine Learning Machine Learning ML ML 59