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Mapa interactiu d'observacions de singnàtids a la costa catalana
Mapa d'observacions del GBIF (Global Biodiversity Information Facility) de diferents espècies de singnàtids al litoral català amb l'hàbitat marí on s'han localitzat.
Mapa d'intensitat dels singnàtids al Mediterrani
Mapa de la intensitat d'observacions del GBIF (Global Biodiversity Information Facility) de les espècies de singnàtids trobades al mar Mediterrani.
Makroekonomik analiz projesi
Türkiye, Meksika ve Brezilya büyüme dinamikleri analizi (2000-2020).
Utilizing Dimension Reduction to understand Key Factors in Paddy Cultivation
The project aims to utilize a particular crop related dataset (Paddy / Rice Dataset from UC Irvene Machine Learning repository utilized in current case), which contains multiple agronomic, environmental, and crop‑related features, for the purpose of dimension reduction. Modern agricultural research increasingly relies on large, feature‑rich datasets to understand crop performance, optimize cultivation practices, and support data‑driven decision‑making. As farming conditions, climate patterns, and crop varieties evolve, the volume and complexity of agricultural yield continues to grow which is an expected practice. For current project, we utilize the full Paddy Dataset because all feature groups—soil characteristics, climate variables, crop breed or traits, and management practices—contribute to understanding paddy or rice growth patterns. Small variations across a few selective features can significantly influence yield, making dimension reduction a valuable tool for uncovering underlying structure in the dataset. And, accordingly the results can be utilized to harness parameters which influence paddy production volume the most for real world cultivation suggestions.
Pengaruh Suhu dan Kelembaban Udara terhadap Curah Hujan di Stasiun Klimatologi Semarang Tahun 2020
Tugas ini disusun sebagai salah satu syarat pemenuhan Ujian Akhir Semester (UAS) mata kuliah Komputasi Statistika 2
Modeling based on the Kaggle Diabetes Dataset: Diabetes Prevalence Classification and Glucose Regression Prediction
WQD7004 Programming for Data Science-Group Project-Group 12 member: LI YONGQI 25060741 LU YUXUAN 25068337 LILUANDONG 25066043 MIXIN 24060896 ZHANG TINGTING 25071760
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