AroniSmartIntelligence™: Speech To Text Transcription Module

AroniSmartIntelligence ™ is one of the most advanced analytics tools with Machine Leaning, Data Science, Statistics, Econometrics,  NLP Text and Sentiment analysis, Neural Network, and Support Vector Machine capabilities. To support NLP Text and Sentiment analysis, a new capability has been added: Speech-to-Text Transcription.

AroniSmartIntelligence Speech Recognition and Transcription is being added to address key requirements and meet the needs for more advanced NLP Text and Sentiment analytics.

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AroniSmartIntelligence™: Econometrics - Marketing Mix Models

AroniSmartIntelligence ™ is one of the most advanced analytics tools with Machine Leaning, Data Science, Statistics, Econometrics,  NLP Text and Sentiment analysis, Neural Network, and Support Vector Machine capabilities.

AroniSmartIntelligence ™, available on Apple's App Store®,  is intended, very useful, and handy for experts, professionals,  and college and graduate students in Statistics, Machine Learning, Quantitative Business Analytics, Data Science, Econometrics, STEM, Operations Research, and other related fields. It includes a detailed Handbook and a well crafted and instructive User's manual. It is a cutting-edge analytical tool for advanced analytics and developing actionable insights without the hassle of coding.

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AroniSmartIntelligence™: Version 12.1.x Econometrics - Marketing Mix Models

Machine Learning and Data Science Models  are gradually and fastly improving and becoming the center of advanced analytics, business intelligence, decision making, management science, data science,  and other areas in which sound informed decisions are needed.  Yet, the area continues to be  both exciting and intriguing, while remaining the needed tool to generate valuable analytical insights to support decision making and advanced research. A critical area includes Marketing Mix predictive models, in which Multiplicative Models and LogLog Models, built on sound Data Scinece capabilities have been the major focus, as businesses try to grow by targeting the right customers and optimally allocating their marketing budget.  Given this increasing  importance of this foundation in the advanced analytics, machine learning and data science, AroniSmartIntelligence ™, one of the most advanced analytics tools with Big Data, Statistics, Econometrics, Machine Leaning, Text and Sentiment analysis, Neural Network, Support Vector Machine capabilities has continually  improved the key modules including  Neural Networks, Econometrics, Time Series, Bayesian Models,  Support Vector Machine, Big Data Analytics,  and Text Analytics. The latest improvements  are  in the new version AroniSmart 12.1.x, available on Apple's App Store®, starting today.  

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AroniSmartIntelligence Stock Market Indices Time Series Support Vector Machine and Neural Network Analysis

After a fueled momentum over 2021, the stock market has started the year 2022 with volatility. The latest Q3 2021 stock market perfomance figures reminded of the increasing market volatility and other dynamics in late Q1 and early Q2, 2021. Major questions coming from AroniSmartIntelligence™ users have over the 2021 year focused on how to use AroniSmartIntelligence capabilities to analyze the connection among the key Stock market indices, especially NASDAQ vs  Dow Jones(DJI), S&P 500,  Russell 2000, Gold,  and Oil.   AroniSmart™ team, leveraging the Machine Learning Time Series capabilities, including Support Vector Machine,  and Neural Network Analysis of AroniSmartIntelligence™ ,  has analyzed the trends of  NASDAQ  and DJI vs  the  other stock indices (DJI, S&P 500, Russell 2000, Oil, Gold)  between  early Jan 2021 and  early Jan 2022 and came up with insights and  projections on the dynamics.   The insights are presented below (for disclaimer and terms, check AroniSoft website. For related analyses of Stock Markets using Time Series, Dominance Analysis, and Neural Network capabilities see here AroniSmartIntelligence™ in Action: Time Series Support Vector Machine and Neural Network Analysis of Stock Market Indices in Q4 2020 - Q4 2021)

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