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Why Artificial Intelligence and Machine Learning?

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Artificial intelligence and machine learning are helping people and businesses achieve key goals, obtain actionable insights, drive critical decisions, and create exciting, new, and innovative products and services. This definitely applies to Artificial Intelligence and Machine Learning as well, and so understanding and describing why these fields should be used for a given need is critical, and then should be followed by how they're used (e.g., processes, algorithms, data scientists), and lastly by what is produced as a result (e.g., product, service, recommendation engine, smart assistant). These days there are many amazing, real-world applications of artificial intelligence and machine learning being deployed to benefit both customers and companies. To learn more about artificial intelligence and machine learning, including driving goals, definitions, types, algorithms, processes involved, important tradeoffs and considerations, and examples of real-world applications for each category, check out my Goal-Driven Artificial Intelligence and Machine Learning class on Skillshare!


When Artificial Intelligence and Social Media Marketing Collide

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Both artificial intelligence and social media marketing are getting a lot of attention nowadays because of their huge benefits and growth potential. This feature can be used in various ways by the brands for developing their social media marketing strategies to further increase the reach and success of their social media marketing campaign. There are many creative social media marketers who are awesome at creating awesome contents. The various AI tools help them to collect the valuable insights from the data collected through various social media platforms to get incredible insights on the customer taste and preferences.


Putting the "Science" Back in Data Science

@machinelearnbot

If you start your data analysis by simply stating hypotheses and applying Machine Learning algorithms, this is the wrong way. In a few words, I studied the past 27 years of Business Management literature and I tried to develop an epistemologically disruptive approach to measure and predict service quality, mixing Business Administration with Electrical Engineering concepts. Ah, profit call be predicted using Deep Neural Networks using data from Market Research, Financial Data and word embeddings from Social Media as features! So, the SCIENCE in Data Science is not only about Machine Learning, Deep Learning, Natural Language Processing, A.I.


Experiential Commerce with Soccer com

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Sachin Lulla 2 views How Old World Industries accelerated processes and expanded business without increasing staff - Duration: 3:34. Sachin Lulla 93 views Metrie provides a stable, scalable & flexible integration platform w IBM Sterling B2B Integrator - Duration: 4:17. How Old World Industries accelerated processes and expanded business without increasing staff - Duration: 3:34. Metrie provides a stable, scalable & flexible integration platform w IBM Sterling B2B Integrator - Duration: 4:17.


Experiential Commerce with Soccer com

#artificialintelligence

Sachin Lulla 9 views How Old World Industries accelerated processes and expanded business without increasing staff - Duration: 3:34. Sachin Lulla 93 views Metrie provides a stable, scalable & flexible integration platform w IBM Sterling B2B Integrator - Duration: 4:17. How Old World Industries accelerated processes and expanded business without increasing staff - Duration: 3:34. Metrie provides a stable, scalable & flexible integration platform w IBM Sterling B2B Integrator - Duration: 4:17.


3 machine learning success stories: An inside look

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Fewer technologies are hotter than artificial intelligence (AI) and machine learning (ML), which mimic the behavior of the human mind to help companies improve business operations. Even Uber, weathering several legal challenges, has made time to reveal Michelangelo, an internal ML-as-a-service platform, that "democratizes machine learning and makes scaling AI to meet the needs of business as easy as requesting a ride." For the past several months, he has been using Salesforce.com's Einstein AI/ML technology to increase personalization across the bank's small business, wholesale, commercial wealth and commercial banking units. Key advice: Using ML to identify patterns is the key to creating self-healing capabilities.


Top 5 Digital Transformation Trends In Manufacturing

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Today, these advanced algorithms are transforming the way the manufacturing industry collects information, performs skilled labor, and predicts consumer behavior. Smart factories with integrated IT systems provide relevant data to both sides of the supply chain more easily, increasing production capacity by 20%. Robots and other automated technology are also integral in improving speed and efficiency, allowing manufacturing companies to "optimize production workflows, inventory, Work in Progress, and value chain decisions." With this new level of predictive accuracy comes an improvement in condition monitoring processes, providing manufacturers "with the scale to manage Overall Equipment Effectiveness (OEE) at the plant level increasing OEE performance from 65% to 85%."


Making Machine Learning Accessible: 3 Ways Entrepreneurs Can Apply It Today

@machinelearnbot

Unlike traditional models, which require specific rules and feature sets to extract meaning from data, deep learning models autonomously draw conclusions and create their own classification rules from unstructured data. Given enough time and data, deep learning models can make sense of virtually any unstructured data set. Now, thanks to the 2.5 quintillion bytes produced per day -- much of it publicly available via Google and YouTube -- and massive improvements in cloud computing technology, deep learning isn't just viable -- it's inevitable, and it's profitable. It uses a four-pronged approach, including data crawling, natural language processing, machine learning and artificial intelligence, to help business leaders optimize prospect data and sell more efficiently.


AI: marketing's friend or foe?

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Many of us will encounter a marketing virtual agent on a near daily basis when being asked qualifying questions or providing automated answers to standard questions, however their potential goes far beyond this and presents exciting opportunities at every stage of the customer journey. Voice assistants create an opportunity to interject compelling content into everyday situations, such as recipes in the kitchen, linked to an ecommerce platform. Recent research has shown that monotonous, repetitive tasks triggers automatic decision making and makes employees more likely to behave unethically. Sure, inertia and lack of technical expertise play a part, but many marketers hold a major question mark over AI's ability to perform a key part of their role: EMPATHY.


Break away from the herd: How smart brands are using AI - Watson

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Many data-savvy brands employ big data and predictive analytics to help identify the next-best action based on customer segments and transactional patterns, which only represents about 20% of known information about customers for most brands. Some leading brands take it a step further and use machine learning along with Artificial Intelligence (AI) technology like IBM Watson's APIs to collect, connect and make sense of the other 80% of the unstructured data such as tweets, Facebook posts, emails, call center audio recordings and other observable customer behaviors, likes and preferences and combine it with their transactional customer data. To make your brand truly delight and engage customers, you'll need to do the following: To learn more about how you can truly supercharge your brand's marketing and customer engagement efforts, download the IBM and SugarCRM white paper: "Becoming a Brilliant Brand Conversationalist." Using AI to supercharge brand engagement Learn how you can truly step up your brand's marketing and customer engagement campaigns with AI Your email address will not be published.Required fields are marked *