Tag: Python
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US Real Estate – Harnessing the Power of AI
The content describes a continuation of the use-case series dedicated to real estate (RE) monitoring, trend analysis, and forecast. It focuses on predicting and estimating US house prices using a pre-trained ML model. The content covers various machine learning algorithms, data preprocessing, model training, and evaluation using the Boston housing price dataset. Key takeaways include…
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ML/AI Wildfire Prediction using Remote Sensing Data
The content is a detailed exploration into the application of machine learning (ML) and artificial intelligence (AI) in predicting wildfires using a dataset acquired in Canada. It covers data preprocessing, ML workflow, exploratory data analysis (EDA), model training, performance evaluation, hyperparameter optimization (HPO), and data resampling techniques like SMOTE and ADASYN. The ML models are…
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Applications of ML/AI in HR – Predicting Employee Attrition
A critical arm of artificial intelligence (AI), machine learning (ML) is making strides in every area of HR. We discuss its role of ML/AI in HR and people-centric transformation. Results have a crucial influence on customer satisfaction and retention, especially when employees come into regular contact with customers. Knowing when employees are most likely to have…
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Towards Optimized ML Wildfire Prediction
Towards Optimized ML Wildfire Prediction: This Python case example stems from the initial research into ML/AI wildfire prediction using the dataset that was downloaded from the UCI Machine Learning Repository.
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Macroaxis AI Investment Opportunity
The research presented examines the portfolio optimization potential of Macroaxis’ new artificial intelligence (AI) system. This tool automates processes like asset allocation, portfolio diversification and rebalancing, and equity research, providing a list of suggested investments. The AI makes suggestions based on market conditions and investor risk tolerance, and has demonstrated higher average returns than the…
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AI-Guided Drug Recommendation
AI-Guided Drug Recommendation in Python using NLP text processing. Key steps: WordCount images, NLP Pre-Processing, NER via spacy, LDA topic modelling, and Word2Vec Vectorization for reviews using pretrained glove model. Input data: the Kaggle UCI ML Drug Review dataset. Applications in the pharmaceutical industry, including drug R&D, drug repurposing, improving pharmaceutical productivity, and clinical trials,…
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ANOVA-OLS Prediction of Surgical Volumes
Operating rooms (ORs) are some of the most valuable hospital assets, generating a large part of hospital revenue. Statistical models have been developed using datasets to predict daily surgical volumes weeks in advance. We focus on the VUMC dataset for evaluation of our statistical models. We use the ANOVA null-hypothesis test for the total number…
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Drug Review Data Analytics
UCI Drag Review Data Analytics An AI assisted medication recommender framework is truly vital with the goal that it can assist specialists and help patients to build their knowledge of drugs on specific health conditions. We Build a Drug Recommendation System that recommends the most effective drug for a certain condition based on available reviews…
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Quant Trading using Monte Carlo Predictions and 62 AI-Assisted Trading Technical Indicators (TTI)
Algorithmic Trading using Monte Carlo Predictions and 62 AI-Assisted Trading Technical Indicators (TTI): The goal of the here presented pilot study is to develop and test an end-to-end Python-3 script in Jupyter that implements algorithmic trading. Thanks to high-level automation and integration of multiple tasks, the script can simultaneously analyze hundreds of technical indicators, run…
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Simple E-Commerce Sales BI Analytics
Good businesses learn from previous efforts and test future ideas using e-commerce analytics (ECA). ECA enable you to delve deep into historical BI data, and future forecasting so that you can make the optimized business decisions. The key benefits of ECA are as follows: Let’s look at the warehouse optimization problem by analyzing Kaggle sales…
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Bear Market Similarity Analysis using Nasdaq 100 Index Data
We calculate similarities between the current market conditions and the selected six historical bear market events using the Nasdaq 100 Index Data. Results suggest that Covid19 pandemic, 1987 black Monday, and 1990 recession are closest to the current bear market.
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Basic Stock Price Analysis in Python
Our basic stock price analysis in Python includes stock prices, stock volume, market capitalization, 50/200-day moving average, scattered X-plot matrix, and stock volatility or standard deviation.
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Predicting Trend Reversal in Algorithmic Trading using Stochastic Oscillator in Python
This is the example stochastic oscillator in Python for algorithmic trading $NVIDIA candlestick chart vs a stochastic oscillator chart over our trading period.
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Brazilian E-Commerce Showcase
This is a hands-on end-to-end Brazilian e-commerce use-case with detailed Exploratory Data Analysis (EDA) steps and business action items. We apply the RFM Segmentation and Customer Analysis to the Brazilian E-Commerce Public Dataset by Olist. It focuses on the lifetime value of customers, and it’s the preferred customer segmentation methodology for eCommerce businesses that focus…
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Customer Churn/Retention Rate ML/AI Strategies that Work!
Telco Customer Churn/Retention Rate ML/AI Strategies that Work! Machine learning could predict customers with high probability to churn! Cohort analysis is a way to understand customer churn (aka attrition). In doing so, we maximize the ratio max [ (Customer Retention Rate)/(Customer Churn Rate) ]
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The Application of ML/AI in Diabetes
The study uses machine learning (ML) to predict diabetes in patients. Classifying diabetics is complex, but ML can offer quick and accurate predictions. The study focuses on type 2 diabetes and uses the Pima Indians database for diagnostic measurements. Models were trained with Python and the Anaconda library. Feature engineering and exploratory data analysis revealed…
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Inflation-Resistant Stocks to Buy
Inflation-Resistant Stocks to Buy AAPL Example Python workflow Download 3 historical datasets – stock price and monthly/annual CPI Compute the monthly/annual stock performance (%) and CPI rate (%) Apply linear regression to the stock vs CPI performance cross-plot Check the slope or gradient of the linear trend – positive, negative or zero.
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A Shamelessly Simple E-Restaurant Order
This simplest Python online restaurant order system gets your restaurant online fast. So you can keep cooking without sacrificing what matters.
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AI-Powered Customer Churn Prediction
AI-Powered Customer Churn Prediction Churn is a good indicator of growth potential. Churn rates track lost customers, and growth rates track new customers—comparing and analyzing both of these metrics tells you exactly how much your business is growing over time. In this project, we explored the churn rate in-depth and examined an example implementation of…
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AI-Powered Stroke Prediction
Contents: Introduction Stroke, also known as brain attack, happens when blood flow to the brain is blocked, preventing it from getting oxygen and nutrients from it and causing the death of brain cells within minutes. According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally after ischemic heart disease,…
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