rcParams['font.size'] = 22 import seaborn as sns # Suppress warnings from pandas import warnings warnings.filterwarnings('ignore') # Read in the datasets and limit to the first 1000 rows (sorted by SK_ID_CURR) # This allows us to actually see the results in a reasonable amount of time...
🧩 Batch Multiple Embeddings: Introduced 'RAG_EMBEDDING_OPENAI_BATCH_SIZE' to process multiple embeddings in a batch, enhancing performance for large datasets. 🌍 Improved Translations: Enhanced the translation quality across various languages for a better user experience.Fixed...
Note that the statistics (e.g. mean and standard deviation for the Standard Scaler) are computed on the training set only, then both datasets are transformed according to them. This is very important as it avoids leaking any information from the test set into the training process, which ...