Data Science Dojo

MAY 27, 2024

Released in 2018, Duplex garnered attention for its ability to handle real-world scenarios, such as making restaurant reservations, with remarkable accuracy and naturalness.

K-nearest Neighbors 338

K-nearest Neighbors Supervised Learning AI AI 338

Data Science Dojo

AUGUST 16, 2023

2018: Transformer models achieve state-of-the-art results on a wide range of NLP tasks, including machine translation, text summarization, and question answering. Interpretability: Transformer models are not as interpretable as other machine learning models, such as decision trees and logistic regression.

Natural Language Processing 195

Natural Language Processing Decision Trees Deep Learning Deep Learning 195

Data Science Dojo

AUGUST 16, 2023

2018: Transformer models achieve state-of-the-art results on a wide range of NLP tasks, including machine translation, text summarization, and question answering. Interpretability: Transformer models are not as interpretable as other machine learning models, such as decision trees and logistic regression.

Natural Language Processing 195

Natural Language Processing Decision Trees Deep Learning Deep Learning 195

Chatbots Life

MAY 16, 2023

Simple chatbots without generative AI integration rely on pre-programmed responses and rule-based decision trees to guide their interactions with users. Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision.

AI 92

AI AI Natural Language Processing Artificial Intelligence 92

Heartbeat

SEPTEMBER 13, 2023

The " Decision Tree " is a popular example of the rule-based model that offers interpretable insights into how the model arrives at its decisions. Decision trees can be trained and visualized in rule-based explanations to reveal the underlying decision logic. References Castillo, D. Russell, C. &

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Mlearning.ai

APRIL 13, 2023

The transformed data is then passed through a non-linear activation function to classify the data. Gaussian kernels are commonly used for classification problems that involve non-linear boundaries, such as decision trees or neural networks. Why is it important? — Medium

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52