Browsing: Guide

Try the following – ask any Excel user for his/ her favourite Excel formula. More often than not, you will hear just this one name -VLOOKUP.…

For most small- and medium-sized business leaders, the question about AI has shifted. While it used to be “Should we use AI?”, it’s now “Where should…

The success of machine learning pipelines depends on feature engineering as their essential foundation. The two strongest methods for handling time series data are lag features…

def normalize_ws(s: str) -> str: return re.sub(r”\s+”, ” “, s).strip() RAW_DOCS = [ { “doc_id”: “trulens_core”, “title”: “TruLens core idea”, “text”: “TruLens is used to track…

A junior loan officer handling data intake, risk screening, and final decisions alone is prone to mistakes because the role demands too much at once. The…

Donating blood is a lifesaving gift, but it’s not always the easiest one to give. I should know—I’ve been doing it for over 15 years. The…

In this tutorial, we design a practical image-generation workflow using the Diffusers library. We start by stabilizing the environment, then generate high-quality images from text prompts…

Ski mountaineering: Women’s and men’s sprint finals (12:55 and 13:15)Bormio is synonymous with downhill skiing but some athletes will also be attempting to go uphill in…

Suppose you want to locate a particular piece of information in a library that is the size of a city. This is a predicament that businesses…

metadata_dict = metadata.to_dict() diagnostic = DiagnosticReport() diagnostic.generate(real_data=real, synthetic_data=synthetic_sdv, metadata=metadata_dict, verbose=True) print(“Diagnostic score:”, diagnostic.get_score()) quality = QualityReport() quality.generate(real_data=real, synthetic_data=synthetic_sdv, metadata=metadata_dict, verbose=True) print(“Quality score:”, quality.get_score()) def show_report_details(report, title):…