Category: technology
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100 Basic Python Codes
Source: PYPL Popularity of Programming Language, Feb 2024. Table of Contents Setting Up Your Environment Download Datasets Initial Pandas Data QC Displaying Pandas Data Types Showing Descriptive Statistics Exploring the Dataset Email Slicer User Input & Type Conversion Working with Lists Practicing Loops Calculator Temperature Conversion ADC Temperature Sensor Sorting Numpy Arrays Story Generator Display…
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Basic Python Programming
This guide introduces basic concepts and features of the Python programming language. It covers a range of topics, including installation, variables, strings, lists, tuples, sets, dictionaries, loops, conditionals, functions, and modules. The comprehensive content provides valuable information for beginners seeking to learn Python for data science or general programming.
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A Comprehensive Analysis of Best Trading Technical Indicators w/ TA-Lib – Tesla ’23
This study presents a comprehensive stock technical analysis guide for Tesla (TSLA) using the TA-Lib Python library. It explores the use of over 200 technical indicators, analyses historical data, and offers insight for both swing traders and long-term holders. The content includes detailed explanations and plots for various momentum, volume, volatility, and trend indicators, providing…
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Plotly Dash TA Stock Market App
The post explains how to deploy a Plotly Dash stock market app in Python with the dashboard of user-defined stock prices. This includes technical indicators like volume, MACD, and stochastic. The steps include selecting a stock ticker symbol (NVDA), retrieving stock data from yfinance API, adding Moving Averages, saving the stock chart in HTML form,…
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Oracle Monte Carlo Stock Simulations
Oracle Corporation’s significant developments in Generative AI have led to lucrative partnerships with Nvidia and Elon Musk’s xAI. Having secured contracts exceeding $4 billion for its Generation 2 Cloud designed for AI model training, Oracle’s earnings doubled in Q4 2023. Monte Carlo simulations align with Zacks Rank 3-Hold for ORCL, implying bullish potential with projected…
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Time Series Forecasting of Hourly U.S.A. Energy Consumption – PJM East Electricity Grid
Table of Contents PJME Data Let’s set the working directory YOURPATH and import the following key libraries Let’s read the input csv file in our working directory Let’s plot the time series Data Preparation Output: (113926, 1, 9) (113926,) (31439, 1, 9) (31439,) LSTM TSF Let’s plot the LSTM train/test val_loss history Output: MSE: 1811223.125…
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Morocco Earthquake EDA
Featured design via Canva. Clickable Table of Contents Basic Installations and Imports Let’s set the working directory YOURPATH Let’s install and import the following libraries Download Earthquake Input Data For this project, we’ll use a dataset that contains all seismic events over the last seven days, which have a magnitude of 1.0 or greater: Output:…
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Wind Farm AEP Optimization in SciPy – Horns Rev 1 Site
The post outlined the process of optimizing the Annual Energy Production (AEP) of the Horns Rev 1 wind farm using the SciPy algorithm. The results derived from SciPy were cross-validated using other optimizers such as Optuna and PyWake. The study iterates the importance of offshore wind farms in meeting Denmark’s goals of increased electricity generation.
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An Overview of Video Games in 2023: Trends, Technology, and Market Research
The gaming industry is rapidly growing, projected to reach a revenue of $365.6 billion in 2023. Major trends include Web3 gaming, AI integration, and a push for consolidation. Fashion brands collaborate for virtual sales, and advances in gaming technology, such as AR/VR and cloud-based gaming, promise an even more immersive experience for gamers.
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Customer Reviews NLP Spacy Analysis and ML/AI Demand Forecasting of the Steam PC Video Game Service
Steam, a leading digital distribution platform for PC gaming, has seen over 6000 new games released in 2022, averaging over 34 games each day. This post aims to conduct comprehensive customer reviews NLP sentiment analysis and ML/AI demand forecasting using public-domain datasets. It covers EDA, NLP Spacy analysis, ML/AI pipeline, model validation, word clouds, and…
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Datapane Stock Screener App from Scratch
This content provides a quick guide for value investors to use the Datapane stock screener API in Python. It includes instructions for installation, importing standard libraries, setting the stock ticker, downloading stock Adj Close price, and creating visualizations. The post also describes how to build a powerful report using Datapane’s layout components.
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Unsupervised ML, K-Means Clustering & Customer Segmentation
Table of Clickable Contents Motivation Methods Open-Source Datasets This file contains the basic information (ID, age, gender, income, and spending score) about the customers. Online retail is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. The company mainly sells unique all-occasion…
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Risk-Aware Strategies for DCA Investors
Dollar-Cost Averaging (DCA) is an investment approach that involves investing a fixed amount regularly, regardless of market price. It offers benefits such as risk reduction and market downturn resilience. It’s useful for beginners and can be combined with other strategies for a disciplined investment approach. References include Investopedia and Yahoo Finance.
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A Closer Look at the Azure Cloud Portfolio – 3. Azure DevOps Boards
Azure Boards (AB), part of Azure DevOps suite, is a tool for managing software development work that allows planning, tracking, customization, and discussion. The post outlines how to start with AB, set up a project, create and manage work items, customize a project’s boards, and organize work into sprints. AB’s key advantages include its flexibility,…
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GPT & DeepLake NLP: Amazon Financial Statements
The post outlines the implementation of an AI-powered chatbot using NLP to process and analyze financial data from Amazon’s financial statements. The tool employs LlamaIndex and DeepLake to answer queries, summarize financial information, and analyze trends. This approach enhances the efficiency of data analysis, making it a valuable resource for finance and banking professionals.
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A Closer Look at the Azure Cloud Portfolio – 2. From VMs to Web Servers
This guide explains how to create virtual machines (VMs) for deploying web servers from Azure. It covers the process of creating a VM and connecting it to a secured subnet within a virtual network (VNet), using Azure’s Bastion service for secure RDP/SSH connections, and installing a Nextcloud server on the VM. Additional steps include making…
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Working with FRED API in Python: U.S. Recession Forecast & Beyond
The FRED API, or Federal Reserve Economic Data, provides over 267,000 economic time series from 80 sources, offering a wealth of data to promote economic education and research. It encompasses U.S. economic and financial data, including interest rates, monetary indicators, exchange rates, and regional economic data. Additionally, we analyzed correlations, trained currency exchange prediction models,…
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Dabl Auto EDA-ML
Dabl, short for Data Analysis Baseline Library, is a high-level data exploration library in Python that automates repetitive data wrangling tasks in the early stages of supervised machine learning model development. Developed by Andreas Mueller and the scikit-learn community, it facilitates data preprocessing, advanced integrated visualization, exploratory data analysis (EDA), and ML model development, demonstrated…