datasets import MNIST from torchvision.transforms import ToTensor import pytorch_lightning as pl from pytorch_lightning.loggers import WandbLogger class LitAutoEncoder(pl.LightningModule): def __init__(self, lr=1e-3, inp_size=28, optimizer="Adam"): super().__init__() self.encoder = nn....
importjsonfromdataprofilerimportData,Profilerdata=Data("your_file.csv")# Auto-Detect & Load: CSV, AVRO, Parquet, JSON, Text, URLprint(data.data.head(5))# Access data directly via a compatible Pandas DataFrameprofile=Profiler(data)# Calculate Statistics, Entity Recognition, etcreadable_report=prof...
import numpy as np import matplotlib.pyplot as plt from sklearn import datasets from sklearn.cluster import DBSCAN #matplotlib inline X1, y1=datasets.make_circles(n_samples=5000, factor=.6, noise=.05) X2, y2 = datasets.make_blobs(n_samples=1000, n_features=2, centers=[[1.2,1.2]], c...
from sklearn.feature_selection import f_classif import pandas as pd from sklearn.datasets import load_breast_cancer import matplotlib.pyplot as plt X, y = load_breast_cancer(return_X_y=True) df = pd.DataFrame(X, columns=range(30)) df['y'] = y fval = f_classif(X, y) fval = pd....
Are there plans to include Guide datasets as part of the beta? We currently use API access to pull much of our data into BigQuery, but Guide doesn't have the same API coverage as ticket data so we'd appreciate more export options for that data that would allow us to better track ...
Another regularization approach, OHT [37], applies the so-called extended Hough transform on a list of ordered boundary points that enable to detect arbitrary building directions and extract different boundary segments. The comparison metrics considered are the building corners geometric accuracy (RMSE)...
They utilize their analytical, statistical, and programming skills to collect, analyze, and interpret large datasets. They then use this information to develop data-driven solutions to challenging business problems. Part of these solutions is developing machine learning algorithms that generate new insight...
It supports SQL-based queries for precise data retrieval, batch analytics for processing large datasets, and reporting dashboards for visualizing key metrics and trends. Additionally, it facilitates machine learning applications, allowing for advanced data analysis and predictive insights. By providing the...
You can find a whole range ofdata science projectsto work on at DataCamp. These allow you to apply your coding skills to a wide range of datasets to solve real-world problems in your browser, and you can filter specifically by those that require Python. ...
from sklearn.datasets import make_classificationfrom sklearn.decomposition import PCAimport numpy as npimport pandas as pdfrom imblearn.combine import SMOTEENN 报cannot import name 'DistanceMetric' from 'sklearn.metrics'。 先用pip list看看版本 ...