IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others. Naïve Bayes algorithms include decision trees , which can actually accommodate both regression and classification algorithms.

Machine Learning 97

Machine Learning Machine Learning Supervised Learning Clustering 97

Pickl AI

MAY 10, 2023

Decision Trees Decision Trees are non-linear model unlike the logistic regression which is a linear model. The use of tree structure is helpful in construction of the classification model which includes nodes and leaves. Consequently, each brand of the decision tree will yield a distinct result.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Dataconomy

JUNE 13, 2023

It leverages the power of technology to provide actionable insights and recommendations that support effective decision-making in complex business scenarios. At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs.

Power BI 103

Power BI Artificial Intelligence Artificial Intelligence Data Analysis 103

Pickl AI

JULY 12, 2024

Public Datasets: Utilising publicly available datasets from repositories like Kaggle or government databases. Decision Trees Decision trees recursively partition data into subsets based on the most significant attribute values. Web Scraping : Extracting data from websites and online sources.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

NOVEMBER 18, 2024

Structured data refers to neatly organised data that fits into tables, such as spreadsheets or databases, where each column represents a feature and each row represents an instance. Selecting an Algorithm Choosing the correct Machine Learning algorithm is vital to the success of your model. For a regression problem (e.g.,

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

SEPTEMBER 12, 2024

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping. Data Cleaning: Raw data often contains errors, inconsistencies, and missing values.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Businesses need to analyse data as it streams in to make timely decisions. Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). This diversity requires flexible data processing and storage solutions.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52