IBM Journey to AI blog

AUGUST 12, 2024

Their primary objective is to optimize and streamline IT operations workflows by using AI to analyze and interpret vast quantities of data from various IT systems. Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data.

Big Data 106

Big Data Big Data ML ML 106

DagsHub

JULY 25, 2024

Notable Use Cases in the Industry Keras is widely used in industry and academia for various applications, including image and text classification, object detection, and time-series prediction. Companies like Netflix and Uber use Keras for recommendation systems and predictive analytics. Further Reading and Documentation H2O.ai

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

How to Learn Machine Learning

APRIL 26, 2025

This includes duplicate removal, missing value treatment, variable transformation, and normalization of data. Tools like Python (with pandas and NumPy), R, and ETL platforms like Apache NiFi or Talend are used for data preparation before analysis.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

SEPTEMBER 10, 2024

This feature allows users to connect to various data sources, clean and transform data, and load it into Excel with minimal effort. Power Query’s AI capabilities automate repetitive data preparation tasks, such as removing duplicates, filtering data, and combining data from multiple sources.

Power BI 52

Power BI Data Analysis Data Analysis AI 52

Pickl AI

OCTOBER 3, 2024

The process typically involves several key steps: Model Selection: Users choose from a library of pre-trained models tailored for specific applications such as Natural Language Processing (NLP), image recognition, or predictive analytics. Computer Vision : Models for image recognition, object detection, and video analytics.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Pickl AI

JUNE 18, 2024

It now allows users to clean, transform, and integrate data from various sources, streamlining the Data Analysis process. This eliminates the need to rely on separate tools for data preparation, saving time and resources. AI-powered Power BI projects make this a reality. How Can AI be Integrated With Power BI Projects?

Power BI 52

Power BI Data Analysis Data Analysis Data Visualization 52

Pickl AI

JULY 12, 2024

Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes. This section explores the essential steps in preparing data for AI applications, emphasising data quality’s active role in achieving successful AI models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52