Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
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from abc import ABC | |
from typing import List, Optional, Any | |
import chromadb | |
from langchain.docstore.document import Document | |
from langchain.embeddings.base import Embeddings | |
from langchain.vectorstores import Chroma | |
class CachedChroma(Chroma, ABC): |
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from metaflow import FlowSpec, step, IncludeFile | |
def dataset_wine(): | |
from sklearn import datasets | |
return datasets.load_wine(return_X_y=True) | |
def model_knn(train_data, train_labels): | |
from sklearn.neighbors import KNeighborsClassifier | |
model = KNeighborsClassifier() | |
model.fit(train_data, train_labels) |
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# principal amount | |
p = 10_000 | |
# annual rate of interest | |
r = 0.05 | |
# number of years | |
t = 5 |