Category: Data-Driven Tech
-
Marketing Q3 ’22 Round-Up
This is review of Marketing Q3 ’22 trends: medium digest Hubspot Insights All of SEO
-
Risk/Return POA – Dr. Dividend’s Positions
Based upon the Portfolio Optimization Algorithm (POA) discussed earlier and the relevant POA QC analysis and comparisons, let’s look at the current stock positions suggested by Dr. Dividend (DD). Let’s define the following POA parameters: benchmark_ = [“^GSPC”,]portfolio_ = [‘AAPL’, ‘GOOG’, ‘COST’, ‘SBUX’, ‘DE’,’SOFI’,’APD’,’UNH’,’SHW’,’NVDA’] start_date_ = “2021-01-01”end_date_ = “2022-10-05”number_of_scenarios = 10000 trade_days_per_year = 252 delta_risk…
-
ML/AI Credit Risk Analytics
This project utilized a variety of machine learning algorithms (RF, KNN, DT, GB, LR, ANN, and SVM) to create credit risk modeling for efficient credit rating. Among these, the Gradient Boosting algorithm showed the highest test accuracy at 81.7%. The project also produced feature importance coefficients that reflect relevant credit ratings or probability of default,…
-
HealthTech ML/AI Q3 ’22 Round-Up
Featured Photo by Andy Kelly on Unsplash This blog presents a Q3 ’22 summary of current healthtech ML/AI innovation methods, trends and challenges. Virtual reality, artificial intelligence, augmented reality, and machine learning are all healthcare technology trends that are going to play a vital role across the entire healthcare system. Let’s take a look at…
-
Portfolio Optimization Risk/Return QC – Positions of Humble Div vs Dividend Glenn
The Portfolio Optimization Algorithm (POA) is used for comparing the top five stock positions of Humble Div (HD) and Dividend Glenn (DG) from 2017 to 2022. The Risk/Return Ratio (RRR) shows HD portfolio as a better performer than DG portfolio and the market. Both portfolios and market are within risk boundaries.
-
The MobiDev ML Approach to Demand Forecasting Demystified
This post outlines MobiDev’s machine learning framework for marketing-driven demand forecasting (DF), consisting of five steps. The process begins with an overview of input data and setting KPIs, followed by data preparation and exploratory analysis. DF models are then trained, tested, and cross-validated, concluding with their final deployment. The approach incorporates business-specific factors like product…
-
Risk/Return QC via Portfolio Optimization – Current Positions of The Dividend Breeder
Featured Image by AbsolutVision on Unsplash Based on the Portfolio Optimization Algorithm (POA) discussed earlier, let’s run the QC test of current positions of The Dividend Breeder in terms of the Risk/Return Ratio (RRR). The POA input is as follows: benchmark_ = [“^GSPC”,]portfolio_ = [‘SCHD’, ‘O’, ‘MSFT’, ‘TGT’, ‘MCD’, ‘PFE’, ‘CSCO’, ‘USB’, ‘KO’, ‘ABBV’,‘CVX’, ‘VZ’,…
-
Stock Portfolio Risk/Return Optimization
The content describes the implementation of an end-to-end Python stock optimization workflow, including steps like importing libraries, setting up key variables, downloading and cleaning stock data, portfolio analysis, and visual representation of the best portfolio. The script aims to minimize the Risk/Return ratio with respect to a market benchmark, providing an efficient way to assess…
-
EdTech for All: Free/Paid IoT Courses
The Internet of Things (IoT) is a rapidly expanding field, with over 10 billion active devices in 2021. By 2030, this figure is expected to exceed 25.4 billion. The impact of IoT solutions could result in $4-11 trillion economic value by 2025. Numerous Massive Open Online Course (MOOC) platforms offer courses related to the IoT,…
-
Invest in AI via Macroaxis Sep ’22 Update
Invest in AI via Macroaxis Sep ’22 Update 4 AI pillars AI thematic idea 20 stocks Asset Allocation Market Capitalization (%) Instrument Composition Market Elasticity Risk/Return Ratio Asse ratings Technical Analysis Correlation Matrix Takeaways Business headlines
-
ML/AI Diamond Price Prediction with R
The post discusses an analysis for determining the price of diamonds, aiming to detect possible overpayment. Using R Studio and various machine learning models, including linear regression, XGBoost, SVM, Decision Tree, and Random Forest, the study targets diamonds’ price and related factors. The best performance is provided by the Random Forest model, indicating the primary…
-
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…
-
Gulf’s Oil Price Web Scraping in R
Gulf’s Oil Price Web Scraping in R. Gulf states to gain $1.3 trillion in additional oil revenue by 2026: IMF. We discuss the basics of sourcing oil market price data for free online. discuss the basics of sourcing oil market price data for free online. Webscraping in R is a technique to retrieve large amounts…
-
Cloud-Native Tech Status Update Q3 2022
Cloud Computing Trends Q3 2022, market Share update key services IaaS PaaS FaaS Saas Cloud digital transformation all-the-way DevSecOps CI/Cd GitLab MLOps IoT Tech GCP gateway Big data Deloitte use-cases Stock markets Health Tech Cybersecurity Highlights Events Webinars AWS Storage E-training
-
10 AI-Powered Websites for Content Writers
The content introduces ten innovative AI-powered websites, including Magic Eraser for image editing, Craiyon for AI-generated drawings, Rytr for fast content creation, Thing Translator for language translation via images, AutoDraw for automatic sketching, Fontjoy for AI-based font pairing, Talk to Books for referencing a collection of over 100,000 books, ‘This Person Does Not Exist’ for…
-
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…
-
Cybersecurity Round-Up
Cybersecurity Summer 2022 Round-Up Palo Alto Networks Security Automation: Within Our Own SOC AT&T SASE Branch with Fortinet DevOps.com webinars: Modern Data Protection With Metallic DMaaS Top 5 Cloud-Native Risks IT GRC Forum Utilizing the NIST Framework for Full-Cycle Privilege Orchestration Snowflake Security Digital Shadows Digest ksqlDB AIaaS Data Security Security Boulevard Webinars E-Training Opportunities
-
The Qullamaggie’s TSLA Breakouts for Swing Traders
The content explains a Python-based stock scanner project that analyses TSLA’s historical data downloaded from Yahoo Finance. It applies a set of functions to identify stocks meeting growth criteria and checks for consolidation. The output is a series of plots showing original close price vs filtered data or breakouts. The scanner aims to help swing…
-
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…
-
Marketing Summer 2022 Update
Hubspot Marketing Summer 2022 Update: Brand Consistency 4 Personalization Trends + Tips US Consumer Trends 20 Content Marketing Examples 9 Automation Trends Top Shopping Trends 8 Easy SEO Basics Social Media Checklist Social Media Daily Checklist SME Marketing Ideas Tik-Tok Marketing Highlights YouTube Thumbnail Ecommerce SEO Strategy ABM Strategy Job Simulations – HR 20 Webinar…
Our Blogs 