IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 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

Heartbeat

SEPTEMBER 28, 2023

In a typical MLOps project, similar scheduling is essential to handle new data and track model performance continuously. Load and Explore Data We load the Telco Customer Churn dataset and perform exploratory data analysis (EDA). Are there clusters of customers with different spending patterns? #3.

Support Vector Machines 52

Support Vector Machines Machine Learning Machine Learning ML 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