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Data Science

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Last Updated: Mar 13, 2023

Data Engineering Concepts, Processes, and Tools

Data Governance: Concept, Models, Framework, Tools, and Implementation Best Practices

Hotel Price Prediction: Hands-On Experience of ADR Forecasting

Data Science

Data Architect: Role Description, Skills, Certifications and When to Hire

Data Science

Language Models, Explained: How GPT and Other Models Work

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

Occupancy Rate Prediction: Building an ML Module to Analyze One of the Main Hospitality KPIs

The Good and the Bad of Apache Airflow Pipeline Orchestration

The Good and the Bad of Apache Kafka Streaming Platform

Medical Datasets for Machine Learning: Aims, Types and Common Use Cases

Data Science

Generative AI Models Explained

Knowledge Graphs: The Essential Guide

AI in Drug Discovery and Repurposing: Benefits, Approaches, and Use Cases

What is Data Fabric: Architecture, Principles, Advantages, and Ways to Implement

The Good and the Bad of Hadoop Big Data Framework

Data Science

AI in Manufacturing: 5 Successful Use Cases of AI-Based Technologies

Data Mesh Architecture: Concept, Main Principles, and Implementation

Travel Fraud Protection: Key Types of Travel Scam, Protective Measures, and Software to Consider

Data Science

Machine Learning Metrics: How to Measure the Performance of a Machine Learning Model

Conversational AI: How Advanced Chatbots Work

Length of Stay in Hospital: How to Predict the Duration of Inpatient Treatment

Data Science

Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

Data Science

Data Integrity: Types, Threats, and Countermeasures

Responsible AI: Ways to Avoid the Dark Side of AI Use

Short-Term and Vacation Rental Data: Sources and Analysis

Data Science

Synthetic Data for Machine Learning: Its Nature, Types, and Means of Generation

Last Updated: Mar 21, 2022

Time Series Analysis and Forecasting: Examples, Approaches, and Tools

Data Science

Semi-Supervised Learning, Explained with Examples

Data Science

Last Updated: Mar 01, 2022

Demand Forecasting Methods: Using Machine Learning to See the Future of Sales

Federated Learning: The Shift from Centralized to Distributed On-Device Model Training

Analytics Engineer: Job Description, Skills, and Responsibilities

Data Labeling in Machine Learning: Process, Types, and Best Practices

Data Science

AutoML: How to Automate Machine Learning With Google Vertex AI, Amazon SageMaker, H20.ai, and Other Providers

Data Science

Last Updated: Nov 26, 2021

How to Organize Data Labeling for Machine Learning: Approaches and Tools

Data Virtualization: Process, Components, Benefits, and Available Tools

Data Science

Document Classification With Machine Learning: Computer Vision, OCR, NLP, and Other Techniques

Data Lakehouse: Concept, Key Features, and Architecture Layers

Data Science

Data Scientist vs Data Engineer: Differences and Why You Need Both

Natural Language Processing in Healthcare: Using Text Analysis for Medical Documentation and Decision-Making

Data Science

Deep Learning and the Future of Artificial Intelligence

Data Science

IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

What is Data Hub: Purpose, Architecture Patterns, and Existing Solutions Overview

Data Science

Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

Data Science

Natural Language Processing: A Guide to NLP Use Cases, Approaches, and Tools

Flight Price Predictor: Training Models to Pinpoint the Best Time for Booking

Data Science

Predictive Lead Scoring: Discovering Best-Fit Prospects with Machine Learning

Data Science

Data Marts: What They Are and Why Businesses Need Them

Data Science

7 Best Practices to Use While Annotating Images

Data Science

Recommender Systems: Behind the Scenes of Machine Learning-Based Personalization

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