Data Science Dojo

FEBRUARY 15, 2023

as defined by Belinda Goodrich, 2021) are: Project life cycle, Integration, Scope, Schedule, Cost, Quality, Resources, Communications, Risk, Procurement, Stakeholders, and Professional responsibility / ethics. But for more complicated problems, the interdisciplinary field of project management might be useful–i.e.,

K-nearest Neighbors 195

K-nearest Neighbors Decision Trees Support Vector Machines Data Science 195

Flipboard

MAY 26, 2025

An ensemble of machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), were used to evaluate the effects of climate variability and land use on annual water yield. The study revealed significant land cover changes over a 30-year period. km2 (0.24%) to 41.57 km2 (10.38%).

Machine Learning 65

Machine Learning Machine Learning Support Vector Machines 65

Smart Data Collective

JULY 7, 2022

Game Stop in early 2021 comes to mind. Ramneet Rekhi of New York University and his colleagues from Stanford discussed this in their paper titled Finding Undervalued Stocks with Machine Learning. The authors concluded that nonlinear support vector machines can help investors choose investments with the best future returns.

Analytics 145

Analytics Analytics Data Mining Data Mining 145

Towards AI

JULY 20, 2023

This includes one paper from 2020 that conducted feature extraction using a denoising autoencoder alongside a deep neural network, and a flattened vector and support vector machines to evaluate study relevance. Additionally, data extraction can be more difficult to automate than other SLR elements.

Natural Language Processing 96

Natural Language Processing ML ML Support Vector Machines 96

Becoming Human

MARCH 16, 2023

Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. In 2021, 13 AI-derived biologics reached the clinical stage, with their therapy areas including COVID-19, oncology, and neurology. AI drug discovery is exploding.

AI 139

AI AI Deep Learning Deep Learning 139

Mlearning.ai

APRIL 8, 2023

The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. These included the Support vector machine (SVM) based models. These algorithms treated NLP analysis with a more statistical and mathematical approach. 2018) “ Language models are few-shot learners ” by Brown et al.

Natural Language Processing 98

Natural Language Processing Algorithm Machine Learning Machine Learning 98

Mlearning.ai

JUNE 14, 2023

LLMs (Foundational Models) 101: Introduction to Transformer Models Transformers, explained: Understand the model behind GPT, BERT, and T5 — YouTube Illustrated Guide to Transformers Neural Network: A step by step explanation — YouTube Attention Mechanism Deep dive.

Natural Language Processing 52

Natural Language Processing ML ML Support Vector Machines 52