Pickl AI

AUGUST 1, 2023

Machine Learning algorithms, including Naive Bayes, Support Vector Machines (SVM), and deep learning models, are commonly used for text classification. Text Mining Tools and Libraries Various tools and libraries have been developed to facilitate text-mining tasks.

Data Analysis 52

Data Analysis Data Analysis Python Support Vector Machines 52

Pickl AI

JULY 12, 2024

Pandas: A powerful library for data manipulation and analysis, offering data structures and operations for manipulating numerical tables and time series data. Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

Machine Learning 80

Machine Learning Machine Learning Data Science Big Data 80

Pickl AI

JULY 31, 2023

Understanding Eager Learning Eager Learning, also known as “Eager Supervised Learning,” is a widely used approach in Machine Learning. In this paradigm, the model is trained on a labeled dataset before making predictions on new, unseen data. What Are The Advantages of Eager Learning?

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

SEPTEMBER 23, 2024

Synergy Between Artificial Intelligence and Data Science AI and Data Science complement each other through their unique but interconnected roles in data processing and analysis. Data Science involves extracting insights from structured and unstructured data using statistical methods, data mining, and visualisation techniques.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52