Tag: technology
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Cloud-Native Tech Autumn 2022 Fair
Let’s dive deeper into the cloud-native tech trends and features to follow in Q4 2022 and beyond. Contents: Markets Services Serverless Cybersecurity DevSecOps ML/AI/IoT Use-Cases Events Training Explore More Infographic
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Top 10 Most Upvoted Apps Sept ’22
Following Leon Zucchini, let’s consider the latest roundup of the 10 most upvoted brand-new apps, hits on ProductHunt in September 2022. These are xTiles Polywork MeltingSpot Arcade Appwrite Jimo Popsy Typed Growth.Design and of course the best search engine Curiosity.
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Technology Focus Weekly Update 16 Oct ’22
Get top data-driven technology highlights of the week: new SaaS products, tech business applications and learnings of the week: DevOps, DevSecOps, Cybersecurity, public cloud platforms (AWS/GCP/Azure), MarTech, ML/AI, MLOPs, NLP, edtech, e-courses, upcoming events, and related Infographics. Contents: DevOps November 8th, 2022 | 11 a.m. ET Providing reliable and secure services doesn’t just happen. Traditionally,…
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A Comparison of ML/AI Diabetes-2 Binary Classification Algorithms
The post discusses the increasing urgency to diagnose and treat Type-2 Diabetes (T2D), particularly in developing nations. It delves into the use of data-driven techniques, including ML/AI, in processing T2D data. Different ML/AI methods including DNN, SVM, and DT are applied to the Kaggle PIMA Indian Diabetes (PID) dataset, and performance is assessed using Python…
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Bear vs. Bull Portfolio Risk/Return Optimization QC Analysis
Based on the Portfolio Allocation and Optimization Algorithm discussed earlier and the related portfolio management, let’s run the Bear vs. Bull QC test of the portfolio P=[MSFT, AAPL, NDAQ] in terms of the Risk/Return Ratio (RRR). We have got a Sharpe ratio of less than one that is considered unacceptable or bad. The risk the…
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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…
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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,…
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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…
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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,…
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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
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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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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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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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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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K-means Cluster Cohort E-Commerce
K-means Clusters – Cohort Analysis applied to E-Commerce Understanding who your customers are and what they want is a fundamental part of any successful business. It can become increasingly challenging to create a one-size-fits-all customer profile. This is where the concept of cluster-based cohort analysis comes in.
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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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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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Diabetes Prediction using ML/AI in Python
The post focuses on developing a machine-learning model to predict diabetes using patient diagnostic data from the UCI Machine Learning Repository, featuring blood tests and obesity metrics. Implemented classifiers include a random forest, decision tree, XGBoost, and an SVM. The model is trained on this data, achieving highest accuracy with the random forest method (approx.…
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