import torch import torch.nn as nn import pandas as pd import numpy as np from torch.utils.data import Dataset, DataLoader from torchvision import transforms from PIL import Image import os import cv2 from collections import defaultdict import matplotlib.pyplot as plt import torchvision.models as models from torch.optim.lr_scheduler import CosineAnnealingLR # This is for the progress bar. from […]
Tag: kaggle
Li Mu leaf classification kaggle
import torch import torch.nn as nn import pandas as pd import numpy as np from torch.utils.data import Dataset, DataLoader from torchvision import transforms from PIL import Image import os import matplotlib.pyplot as plt import pylab import torchvision.models as models # This is for the progress bar. from tqdm import tqdm import seaborn as sns from […]
[kaggle combat] Titanic’s journey through time and space: a magical algorithm that predicts the fate of passengers
Titanic spaceship Purpose: To aid rescuers and recover missing passengers, the challenge is to predict which passengers were abnormally transported using records recovered from the spacecraft’s damaged computer system. 1. Title In this game, you are tasked with predicting whether the passengers of the Titanic spaceship will be transported to another dimension during its collision […]
kaggle novice competition Spaceship Titanic with TFDF high score code transfer
Spaceship Titanic Dataset with TensorFlow Decision Forests This notebook walks you through how to train a baseline Random Forest model using TensorFlow Decision Forests on the Spaceship Titanic dataset made available for this competition. Roughly, the code will look as follows: import tensorflow_decision_forests as tfdf import pandas as pd dataset = pd.read_csv(“project/dataset.csv”) tf_dataset = tfdf.keras.pd_dataframe_to_tf_dataset(dataset, […]
Summary of time series forecasting methods: from theory to practice (with Kaggle classic competition plan)
Datawhale dry information Editor: Yu Tengkai, Proofreader: Lin Yilin Source: Data School THU, Python Data Science This article is about 2,300 words, and it is recommended to read it for 5 minutes This article shares a useful article summarizing time series methods. Hello everyone, I am Dong Ge. Share an informative article summarizing the time […]
kaggle risk control modeling practice (XGB+LGB+RF+LR)
Table of Contents 1. Data reading and preprocessing 1. Data reading 2. Data preprocessing 2. Variable statistics and screening 1. Variable list 2. IV calculation 3. Feature screening 3. Model construction and evaluation 4. Focus on Avoid 10 years of detours 1. Data reading and preprocessing 1. Data reading Use the risk control practice data […]
Pytorch Kaggle house price prediction
Super detailed explanation of pytorch actual Kaggle competition: house price prediction The boss wrote so well, please repost it and record it. Detailed explanation of pytorch actual Kaggle competition: house price prediction Tutorial Name Tutorial Address Machine Learning/Deep Learning [Li Hongyi] Machine learning/deep learning Chinese tutorial (bilingual subtitles) Generative adversarial network [Li Hongyi] Generate Confrontation […]
Summary of time series forecasting methods: from theory to practice (with Kaggle classic competition plan)
Source: Python Data Science This article is about 2,300 words, and it is recommended to read it for 5 minutes This article shares a useful article summarizing time series methods. Hello everyone, I am Dong Ge. Share an informative article summarizing the time series method, including both theory and practice, with cases and practical links. […]
Kaggle Time Series Modeling Case: Predicting Water Availability
Acea Smart Water Analytics Can you predict future water availability? Each data set represents a different type of water body. Since each body of water is different from each other, the associated characteristics are also different. We will notice that its characteristics are different from those of the lake. These differences are expected based on […]
Kaggle project practice: Titanic Project
I plan to learn from kaggle, so I start with the Titanic project. 1. Introduce the corresponding package import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) import seaborn as sns import matplotlib.pyplot as plt 2. Read data Use pd.read_csv to read the data in […]