Freaks City

After completing "Plain Deep Learning and TensorFlow," I gained a basic understanding of fundamental neural network architectures like BP networks, CNNs, and RNNs. The underlying algorithms aren't particularly complex; for instance, BP networks can be understood with basic calculus and probability theory. CNNs incorporate well-establi ...

In this tutorial, we'll explore the fundamental concepts of linear and polynomial regression, two essential techniques in machine learning for modeling relationships between variables. We'll examine their mathematical foundations and practical implementations using Python's scikit-learn library. Regression Analysis Overview Regression analysis ...

k-Nearest Neighbors Algorithm import numpy as np import pandas as pd import matplotlib.pyplot as plt from math import sqrt plt.rcParams['font.sans-serif'] = ['Simhei'] wine_data = {'color_intensity': [14.13, 13.2, 13.16, 14.27, 13.24, 12.07, 12.43, 11.79, 12.37, 12.04], 'alcohol_content': [5.64, 4.28, 5.68, 4.80, 4.22, 2.76, 3.94 ...

Predict sales for November and December 2018. import glob import os import pandas as pd import re import numpy as np import datetime as dt from sklearn.linear_model import LinearRegression import seaborn as sns from matplotlib import pyplot as plt # Set font for Chinese characters plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axe ...

import torch # Initialize a tensor with gradient tracking x = torch.tensor([1.0, 2.0, 3.0, 4.0], requires_grad=True) # Compute a scalar output y = 3 * torch.dot(x, x) # Backpropagation y.backward() # Display gradients print(f"Input tensor: {x}") print(f"Gradients: {x.grad}") Gradinet Management # Zero out gradients b ...