Meine Projekte

from sklearn.ensemble import 
  RandomForestClassifier

model = RandomForestClassifier()
model.fit(X_train, y_train)

import plotly.express as px

fig = px.line(df, x='date', 
  y='cases', title='Cases')
fig.show()

import tensorflow as tf

model = tf.keras.Sequential([
  tf.keras.layers.Conv2D(32),
  tf.keras.layers.MaxPooling2D()
])

import pandas as pd

df = pd.read_csv('sales.csv')
summary = df.groupby('category')
  .agg({'revenue': 'sum'})

from transformers import pipeline

sentiment = pipeline(
  'sentiment-analysis')
result = sentiment(text)

from scipy import stats

t_stat, p_value = stats.ttest_ind(
  group_a, group_b)
print(f'p-value: {p_value}')