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Introduction The field of data science and artificial intelligence (AI) had tremendous success before the COVID-19 pandemic turned the world upside down. As discussions
Introduction Access to and control of data is one of the biggest challenges faced by data analysts and data scientists. Creative, persistent analysts find ways
Introduction: Prediction is a tricky business. You have to step outside of your comfort zone, your fainted vision of the world and see it thorough
Introduction: Humans are wired to make tough decisions bringing all the context and principles to bear. Similarly, can devices apply the available information to make
Introduction: Certain skill sets suit certain positions better than others, and this is why the path to data science is not uniform and can be
Introduction: “You really don’t need maths to get started with AI”. Follow the empirical path of trial and error, it’s a slow process but with
Storage of unstructured data has always posed many challenges in terms of maintaining consistency between structured and unstructured data, managing backup/restore procedure, performance issues, scalability.
5 ways in which machine learning can be used to generate more profitable returns including: portfolio optimization, volatility clustering, price prediction, trading bots and analyzing news sentiment. About Machine Learning in Finance Machine learning is busy taking over multiple industries today. Wherever you look you hear about “intelligent” speakers, cameras, traffic directions, self-driving cars, personal
The United States Presidential Election occurred on Tuesday, November 2. It concluded with a historic victory by former Vice President Joseph Biden and Senator Kamala Harris. The election of Harris to Vice President-Elect is groundbreaking as the first woman, the first woman of color, the first black woman, and the first Asian elected as Vice
Language models in NLP(Natural Language Processing) Systems are Machine Learning based models which are trained to learn and understand Natural Languages like how humans do. A simple example of a trained language model will predict the occurrence of the next word in a sentence. Some of the common Language model use cases are Language Translation
With a pandemic fueled 2020, digital transformation accelerated rapidly, and with increased connectivity, thanks to 5G and faster WiFi and improvements in AI and machine learning, IoT looks set to deepen its roots in our lives and industries.
Artificial Intelligence in primary health care is a hot and trending topic these days, and the healthcare sector is being benefited from it in 2020, and beyond. Here is a a brief overview of what AI is in healthcare.
The Healthcare sector is in a critical requirement of innovative technologies for decision-making to handle COVID-19 epidemic. Machine Learning, IoT, and AI help in getting appropriate recommendations in real-time to keep away from the spread.
AI and automation are definitely bringing some major changes, both positive and negative, to the workplace and to our private lives. It’s naïve to hope that they will only bring good things but getting ready for any possible bad effects they may have is possible and necessary.
Ready to learn Big Data? Browse Big Data Training and Certification Courses developed by industry thought leaders and Experfy in Harvard Innovation Lab. Digital Transformation can mean a lot of different things to different people. But for everyone it means dealing with more data than ever before. Industry 4.0, cloud, robotics, “big data,” artificial intelligence,
Fintech and blockchain technology merge quite well. The number of blockchain fintech startups is soaring, while distributed ledger technologies slowly taking ground in the financial services industry. It will be interesting to see if this technology and smart contracts can live up to their expectations and transform financial ecosystem for the better. Let’s see how smart contracts and blockchain can transform the global FinServ, explore the major blockchain platforms, and check out several fintech startups that use this technology.
1) Tell us about yourself? Like many in the data science profession, I began my career as a physicist. After earning my doctorate at the
Tell us about your background? I have 10 years of experience building analytics solutions, working in consulting, and leading the development of myriad architecture, cloud,