DEEP LEARNING FOR DATA MINING UNSUPERVISED FEATURE LEARNING AND REPRESENTATION

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

MACHINE LEARNING EXPLAINED: A PRACTICAL GUIDE TO DATA-DRIVEN DECISION MAKING

Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis

MACHINE LEARNING APPLICATIONS

Practical Lakehouse Architecture: Designing and Implementing Modern Data Platforms at Scale

MACHINE LEARNING FOR HEALTHCARE PREDICTIVE ANALYTICS AND PERSONALIZED MEDICINE

Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

DEEP LEARNING: NEURAL NETWORK AND BEYOND

Business Statistics and Data Processing

MACHINE LEARNING FOR IMAGE GENERATION AND STYLE TRANSFER

Storytelling with Data: Let's Practice!

REINFORCEMENT LEARNING: FOUNDATIONS, ALGORITHMS AND APPLICATIONS

Driving Data Quality with Data Contracts: A comprehensive guide to building reliable, trusted, and effective data platforms

UNLEASHING THE POWER OF AI: A COMPREHENSIVE GUIDE TO ADVANTAGES AND DISADVANTAGES IN DIFFERENT INDUSTRIES

Bayesian Analysis with Python: A practical guide to probabilistic modeling, Edition 3

MACHINE LEARNING FOR DATA SCIENCE - USING ML ALGORITHMS FOR PREDICTIVE MODELING

Managing Data as a Product: Design and build data-product-centered socio-technical architectures

PRACTICAL MACHINE LEARNING APPLICATIONS

Apache Spark Graph Processing