该项目专注于分析和预测苹果（AAPL）、谷歌（GOOG）、微软（MSFT）、亚马逊（AMZN）和特斯拉（TSLA）等主要科技公司的股票数据。使用的数据是每个股票的历史库存信息、各种度量和先进的机器学习技术。
This project focuses on the analysis and prediction of stock data for major tech companies like Apple (AAPL), Google (GOOG), Microsoft (MSFT), Amazon (AMZN), and Tesla (TSLA). The data used is the historical stock information of each stock, various metrics, and advanced machine learning techniques. (2024-05-03, Jupyter Notebook, 0KB, 下载0次)
使用长短期内存（LSTM）模型预测特斯拉（TSLA）的未来股价，并使用Streamlit仪表板应用程序可视化数据。
Predicting future stock prices of Tesla (TSLA) using a Long Short-Term Memory (LSTM) model, and visualizing the data using a Streamlit dashboard application. (2024-04-21, Jupyter Notebook, 0KB, 下载0次)
使用长短期记忆（LSTM）进行苹果和特斯拉股票价格的时间序列预测涉及根据历史数据训练模型以预测未来价格。LSTM捕获长期依赖性的能力使其适合于此类任务，有助于理解股票价格的复杂模式和趋势。
Using Long Short-Term Memory (LSTM) for time series forecasting of Apple and Tesla stock prices involves training the model on historical data to predict future prices. LSTM s ability to capture long-term dependencies makes it suitable for such tasks, aiding in understanding complex patterns and trends in stock prices. (2024-04-19, Jupyter Notebook, 0KB, 下载0次)
该存储库包含Coursera上“Power&Play:Tesla和GameStop股价和收益的相关性分析”项目的脚本和笔记本。分析特斯拉（TSLA）和GameStop（GME）的股价和收益相关性。提供Python脚本和Jupyter笔记本，用于全面分析。
This repository contains scripts and notebooks for "Power & Play: Correlation Analysis of Tesla and GameStop Stock Prices and Earnings" project on Coursera. Analyze stock prices and earnings correlation of Tesla (TSLA) and GameStop (GME). Python scripts & Jupyter notebooks provided for comprehensive analysis. (2024-04-13, Jupyter Notebook, 0KB, 下载0次)
作为一名为投资公司工作的数据科学家，您将提取特斯拉和GameStop的收入数据，并构建一个仪表板来比较股票价格与收入。
As a data scientist working for an investment firm, you will extract the revenue data for Tesla and GameStop and build a dashboard to compare the price of the stock vs the revenue. (2024-03-04, Jupyter Notebook, 0KB, 下载0次)
作为一名为对冲基金工作的数据科学家，我的任务是提取特斯拉和GameStop的利润数据，并开发仪表板。该仪表盘旨在提供股票价格和相关利润的比较分析，提供股票表现和对冲基金损益之间的动态见解。
As a data scientist working for a hedge fund, my task is to extract profit data for both Tesla and GameStop and develop a dashboard. This dashboard aims to provide a comparative analysis of the stock prices and associated profits, offering insights into the dynamics between stock performance and hedge fund gains or losses. (2024-02-05, Jupyter Notebook, 0KB, 下载0次)
1.这是一个公司（特斯拉）的股票预测项目，它使用LSTM（长短期记忆）预测其股票价格。2.泰坦尼...
1.This is a Stock Prediction Project of a company (TESLA) which predicts its stock price by using LSTM (Long Short-Term Memory). 2.Titanic Classification which predicts the survival of persons. (2023-11-10, Jupyter Notebook, 0KB, 下载0次)
这是我的python项目，研究特斯拉和GAMESTOP的股价和收入。这是Python Project for Da...的最后一项任务...，
This is my python project to look into TESLA and GAMESTOP share price and revenue. This is the final assignment for Python Project for Data Science (2023-10-01, Jupyter Notebook, 0KB, 下载0次)
该代码通过Facebook Prophet机器学习模型设计，以预测未来30天特斯拉的价格，b…，
The code is designed through a Facebook Prophet Machine Learning Model in order to forecast the price of Tesla 30 days into the future, b…, (2023-08-24, Jupyter Notebook, 0KB, 下载0次)
使用过去100天的数据构建LSTM模型来预测特斯拉股票的收盘价。这是从[h..]（https:randerson112358.medium.com使用python-machine-learning-e82a039ac2bb进行股票价格预测）中得到的启发
Build a LSTM model to predict the closing price of Tesla stock using the past 100 days data. This was inspired from [h…](https: randerson112358.medium.com stock-price-prediction-using-python- machine-learning-e82a039ac2bb) (2021-01-12, Jupyter Notebook, 136KB, 下载0次)
本报告用于2010年6月29日至2020年2月3日特斯拉股票价格的探索性数据分析
This repo is for the Exploratory data analysis on the stock prices of Tesla from 2010-06-29 to 2020-02-03 (2021-08-15, Jupyter Notebook, 452KB, 下载0次)
开发了一种深度学习模型，特别适用于特斯拉（Tesla）等自动驾驶汽车，该模型使用全自动系统...
A deep learning model has been developed especially for self-driving cars like Tesla, which uses complete automatic support to drive the vehicle to recognizes traffic signs and follow them properly (2023-02-13, Jupyter Notebook, 2265KB, 下载0次)