Artificial Intelligence

Image by authorLovers of chess, tennis or any other game with two competitors often face this problem — how to pair the players so that the ranking of players is determined in as few games as possible?Similar problems occur in many industries, such as hospitality, food services, education, where entities are to be put onto consumer preference/skill scale, while running as few … [Read more...] about Active sampling for pairwise comparisons

Contemplating the use of AI-based judges in the courtsby Dr. Lance B. EliotFor a free podcast of this article, visit this link https://ai-law.libsyn.com/website or find our AI & Law podcast series on Spotify, iTunes, iHeartRadio, plus on other audio services. For the latest trends about AI & Law, visit our website www.ai-law.legalKey briefing points about this … [Read more...] about AI & Law: Lower Court Judges

In-depth study of decision tree for classification problemDecision Tree. A photo by AuthorIn this article, the decision tree algorithm is the base model for all other tree models. The decision tree comes in the CART (classification and regression tree) algorithm that is an optimized version in sklearn. These are non-parametric supervised learning. The non-parametric means that … [Read more...] about Fully Explained Decision Tree Classification with Python

This week we’re announcing our new partnership with Spell!There is a vast difference between the offline environments where models are trained and production environments where they are served. This training/serving skew often leads to data science teams trying to troubleshoot their models performance once they are deployed. However, most machine learning teams have little to … [Read more...] about Arize AI Partners with Spell to Bring ML Observability to the Spell Platform

For dataset with imbalanced class, we should use precision score rather than accuracy score. A precision score of 1.0 for ‘fraud’ category means that every detected label classified as ‘fraud’ does indeed belong to it. The opposite happens when precision score is approaching 0, which means that the model fail to accurately detect a label that is indeed belong to it.Correction: … [Read more...] about IEEE-CIS Fraud Detection Part III — Balancing the Imbalanced

Image of Airbnb Seattle area, taken from google imagesThere are a lot of steps involved in dealing with any dataset. Some of them are listed below:Importing the librariesLoading and Cleaning the datasetDoing the exploratory data analysis (EDA) over the dataset, to gain some insights about the features and dataUse machine learning models and figure out which one is the best/ or … [Read more...] about Airbnb Seattle Reservation Price Analysis

2. Libraries:We will use Pandas, Numpy, and Scikit-learn libraries. We will import DecisionTreeRegressor class from Scikit-learn to train our dataset.# importing the librariesimport pandas as pdimport numpy as np# Reading the dataset using pandas librariedataset = pd.read_csv('name_of_dataset.csv')3. Exploratory Data Analysis(EDA):Now we will explore our dataset, check it has … [Read more...] about Decision Tree🌳 using Python(for Regression)

AI-DRIVEN ROBOTIC INTELLIGENCEHistorically, mobile manipulators were teleoperated, controlled by an operator from a standoff distance. Today, thanks to enhancements in artificial intelligence (AI) and machine learning, mobile manipulators are on the path to becoming fully autonomous and enhanced with the ability to not only see, but to think and react like humans.When combined … [Read more...] about Keys To Mobile Manipulation: The Ability To Think

In 2013, two researchers from Oxford, Carl Benedikt Frey and Michael A. Osborne, predicted that within the next decade or two, nearly half of the jobs in the U.S. are at risk of being automated. The researchers compiled 702 occupations in the U.S. and got a group of machine learning experts to estimate how susceptible these occupations were to computerization (Frey & … [Read more...] about AI in Education: Building Skills for the Future of Work

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