IBM Journey to AI blog

DECEMBER 20, 2023

Naïve Bayes algorithms include decision trees , which can actually accommodate both regression and classification algorithms. Random forest algorithms —predict a value or category by combining the results from a number of decision trees.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Pickl AI

MAY 30, 2024

Overview of Typical Tasks and Responsibilities in Data Science As a Data Scientist, your daily tasks and responsibilities will encompass many activities. You will collect and clean data from multiple sources, ensuring it is suitable for analysis. This step ensures that all relevant data is available in one place.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

JULY 12, 2024

Data Normalization and Standardization: Scaling numerical data to a standard range to ensure fairness in model training. Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset. classification, regression) and data characteristics.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

SEPTEMBER 12, 2024

C Classification: A supervised Machine Learning task that assigns data points to predefined categories or classes based on their characteristics. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 12, 2024

Statistical Concepts A strong understanding of statistical concepts, including probability, hypothesis testing, regression analysis, and experimental design, is paramount in Data Science roles. Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. What approach would you take?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

JULY 10, 2023

The programming language can handle Big Data and perform effective data analysis and statistical modelling. R allows you to conduct statistical analysis and offers capabilities of statistical and graphical representation. How is R Used in Data Science?

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52