Towards AI

AUGUST 16, 2023

AI engineering is the discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts, which combines the principles of systems engineering, software engineering, and computer science to create AI systems.

AI 98

AI AI Machine Learning Machine Learning 98

AWS Machine Learning Blog

FEBRUARY 25, 2025

Its internal deployment strengthens our leadership in developing data analysis, homologation, and vehicle engineering solutions. To determine the best parameter values, we conducted a grid search with 10-fold cross-validation, using the F1 multi-class score as the evaluation metric.

Algorithm 72

Algorithm Machine Learning Machine Learning K-nearest Neighbors 72

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. Natural Language Processing (NLP) This is a field of computer science that deals with the interaction between computers and human language.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

PyImageSearch

JANUARY 23, 2023

Applying XGBoost to Our Dataset Next, we will do some exploratory data analysis and prepare the data for feeding the model. unique() # check the label distribution lblDist = sns.countplot(x='quality', data=wineDf) On Lines 33 and 34 , we read the csv file and then display the unique labels we are dealing with.

Deep Learning 96

Deep Learning Deep Learning Algorithm Decision Trees 96

Pickl AI

SEPTEMBER 18, 2024

Most professionals in this field start with a bachelor’s degree in computer science, Data Science, mathematics, or a related discipline. These programs provide the fundamental knowledge to understand complex algorithms, data structures, and statistical methods. accuracy, precision, recall, F1-score).

Machine Learning 52

Machine Learning Machine Learning Algorithm Natural Language Processing 52