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.datasets import load_breast_cancer from sklearn.ensemble import RandomForestClassifier from sklearn.inspection import permutation_importance from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt cancer = load_breast_cancer X_train, X_test, y_train, y_test...
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 ...
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. ...
In our case, this was not needed as the datasets were recorded with a fixed camera position. From the set of examples with no visible errors ℰ0E0, we calculate the average segment mask 𝐌 𝑠M¯s for each object instance s of interest from 𝒮intSint. The average mask is ...
These datasets incorporate McCabe and Halstead static code measure metrics. The projects list modules from various programs written in the C or C++ programming languages. Each of these selected files contains 21 independent variables, referred to as features in this study, and one target variable. ...