ODSC - Open Data Science

MARCH 10, 2025

In this hands-on session, youll start with logistic regression and build up to categorical and ordered logistic models, applying them to real-world survey data. Walk away with practical approaches to designing robust evaluation frameworks that ensure AI systems are measurable, reliable, and deployment-ready.

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

Pickl AI

AUGUST 28, 2024

Unlike regression, which deals with continuous output variables, classification involves predicting categorical output variables. They are easy to interpret and can handle both categorical and numerical data. Understand the unique characteristics and challenges of each type to apply the right approach effectively.

Machine Learning 52

Machine Learning Algorithm Categorization Neural Network 52

Pickl AI

SEPTEMBER 17, 2024

It involves tasks such as handling missing values, removing outliers, encoding categorical variables, and scaling numerical features. Explain The Concept of Overfitting and Underfitting In Machine Learning Models. What Is the Role of Explainable AI (XAI) In Machine Learning?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Machine Learning 52

Viso.ai

DECEMBER 6, 2023

Image Classification Image classification tasks involve CV models categorizing images into user-defined classes for various applications. Based on the presence of a tiger, the entire image is categorized as such. Semantic Segmentation Semantic segmentation aims to identify each pixel within an image for a more detailed categorization.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Marktechpost

DECEMBER 11, 2024

Models were categorized into three groups: real-world use cases, long-context processing, and general domain tasks. To ensure safe and responsible use of the models, LG AI Research verified the open-source libraries employed and committed to monitoring AI regulations across different jurisdictions. The safety of EXAONE 3.5

AI Research 85

AI Research AI Researcher Generative AI AI 85

Mlearning.ai

MARCH 24, 2023

The EU AI Act is a proposed piece of legislation that seeks to regulate the development and deployment of artificial intelligence (AI) systems across the European Union. Photo by Guillaume Périgois on Unsplash EU AI Act: History and Timeline 2018 : EU Commission starts pilot project on ‘Explainable AI’.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Categorization Explainability 52

Heartbeat

FEBRUARY 2, 2024

COCO-QA: Shifting attention to COCO-QA, questions are categorized based on types such as color, counting, location, and object. This categorization lays the groundwork for nuanced evaluation, recognizing that different question types demand distinct reasoning strategies from VQA algorithms. In xxAI — Beyond Explainable AI Chapter.

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Viso.ai

APRIL 25, 2024

It’s important to note that the categorization of visual dataset bias can vary between sources. We can define label bias as the difference between the labels assigned to images and their ground truth, this includes mistakes or inconsistencies in how visual data is categorized. This section will use the framework outlined here.

Computer Vision 52

Computer Vision Categorization Algorithm Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

After cleaning, the data may need to be preprocessed, which includes scaling numerical features, encoding categorical variables, and transforming text or images into formats suitable for the model. converting dates into day of the week, creating dummy variables for categorical data). Let’s explore some of the key trends.

Machine Learning 52

Machine Learning Algorithm Data Quality Neural Network 52

Pickl AI

JULY 1, 2024

Decision Trees These tree-like structures categorize data and predict demand based on a series of sequential decisions. Explainable AI (XAI) As models become more complex, XAI techniques will be crucial for understanding how models arrive at their predictions, fostering trust and interpretability in the forecasting process.

Data Science 52

Data Science Neural Network Machine Learning Categorization 52

Mlearning.ai

JANUARY 26, 2023

For categorical input features this is feasible as long as the number of possible values doesn’t grow too big. The values of uminj and umaxj can only be calculated exactly if the entire set of possible values for the input features {i} is available and the corresponding uj values can be calculated in reasonable time.

Explainability 52

Explainability Neural Network Machine Learning Categorization 52

DataRobot Blog

DECEMBER 20, 2022

In this educated example , the aim is to predict home prices at the property level in the city of Madrid and the training dataset contains 5 different data types (numerical, categorical, text, location, and images) and +90 variables that are related to these 5 different groups: Market performance. Property performance. Property features.

Explainability 59

Explainability Automation Machine Learning AI 59

Heartbeat

SEPTEMBER 7, 2023

Here’s a code example that demonstrates how to use Comet for hyperparameter optimization using the Bayes algorithm: import comet_ml from sklearn.datasets import make_classification from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split # Create a dataset X, y = make_classification(n_samples=5000, n_informative=3, (..)

Explainability 52

Explainability Machine Learning Data Scientist Deep Learning 52

IBM Journey to AI blog

FEBRUARY 9, 2024

They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions. Explainable AI is essential to understanding, improving and trusting the output of AI systems.

AI 298

AI AI Generative AI Artificial Intelligence 298