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

IBM Journey to AI blog

JULY 6, 2023

Subcategories of machine learning Some of the most commonly used machine learning algorithms include linear regression , logistic regression, decision tree , Support Vector Machine (SVM) algorithm, Naïve Bayes algorithm and KNN algorithm.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

NOVEMBER 28, 2024

Understanding various Machine Learning algorithms is crucial for effective problem-solving. Familiarity with cloud computing tools supports scalable model deployment. Continuous learning is essential to keep pace with advancements in Machine Learning technologies.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

SEPTEMBER 23, 2024

Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and support vector machines. Hands-On Experience: Practical labs and projects in Python programming, Data Science, and Machine Learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52