DrivenData Labs

MAY 24, 2023

Summary of approach: Our solution for Phase 1 is a gradient boosted decision tree approach with a lot of feature engineering. We used the LightGBM library for boosted decision trees because it has absolute error as a built-in objective function and it is much faster for model training than similar tree ensemble based algorithms.

Machine Learning 225

Machine Learning Machine Learning Data Science Decision Trees 225

IBM Journey to AI blog

JUNE 5, 2024

SaaS takes advantage of cloud computing infrastructure and economies of scale to provide clients a more streamlined approach to adopting, using and paying for software. Software as a service (SaaS) applications have become a boon for enterprises looking to maximize network agility while minimizing costs. Predictive analytics.

Analytics 94

Analytics Analytics AI AI 94

Dataconomy

APRIL 4, 2024

From deterministic software to AI Earlier examples of “thinking machines” included cybernetics (feedback loops like autopilots) and expert systems (decision trees for doctors). Hardware is everywhere : GPUs from gaming, Apple’s M-series chips and cloud computing make immense computing resources trivially easy to deploy.

Algorithm 103

Algorithm AI AI Decision Trees 103

AWS Machine Learning Blog

OCTOBER 30, 2024

Solution overview In this post, we demonstrate how to fine-tune a sentence transformer with Amazon product data and how to use the resulting sentence transformer to improve classification accuracy of product categories using an XGBoost decision tree. Kara is passionate about innovation and continuous learning.

Machine Learning 108

Machine Learning Machine Learning AWS Data Scientist 108

Pickl AI

NOVEMBER 28, 2024

Familiarity with cloud computing tools supports scalable model deployment. Decision Trees These trees split data into branches based on feature values, providing clear decision rules. A solid foundation in mathematics enhances model optimisation and performance.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 4, 2024

A key aspect of this evolution is the increased adoption of cloud computing, which allows businesses to store and process vast amounts of data efficiently. Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees.

Data Science 52

Data Science Data Scientist 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. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70