What is the impact of artificial intelligence (AI) and big data on societies in the Indo-Pacific? How are countries using AI and big data to enhance their national security and advance their national interests? And what are the major regulatory issues? For a perspective on these and other matters, Jongsoo Lee interviewed Simon Chesterman, dean and provost's chair professor of the National University of Singapore Faculty of Law and senior director of AI Governance at AI Singapore. What are nations in the Indo-Pacific doing to develop their artificial intelligence (AI) and big data capabilities?
Package Name: Small Cap Forecast Recommended Positions: Long Forecast Length: 3 Months (7/20/21 – 10/20/21) I Know First Average: 21.48% During the 3 Months forecasted period several picks in the Small Cap Forecast Package saw significant returns. The algorithm had correctly predicted 10 out of 10 returns. The top-performing prediction in this forecast was IKNX, which registered a return of 59.72%. Other notable stocks were MDP and DDS with a return of 44.68% and 34.32%.
In this practical, hands-on course you'll learn how to program using Python for Data Science and Machine Learning. This includes data analysis, visualization, and how to make use of that data in a practical manner. Our main objective is to give you the education not just to understand the ins and outs of the Python programming language for Data Science and Machine Learning, but also to learn exactly how to become a professional Data Scientist with Python and land your first job. We'll go over some of the best and most important Python libraries for data science such as NumPy, Pandas, and Matplotlib NumPy -- A library that makes a variety of mathematical and statistical operations easier; it is also the basis for many features of the pandas library. Pandas -- A Python library created specifically to facilitate working with data, this is the bread and butter of a lot of Python data science work.
A detailed method for extracting sentiment and alignment information from corporate email content. Part 3 -- Shows a method of unsupervised-to-supervised feature extraction. In Part 1 of this series I demonstrated a method for extracting email contents from a proprietary repository in preparation for analysis and further data exploration. In this part I will focus on analysis and rating of the extracted information to determine usability for building a supervised modeling dataset. Currently, the data we retrieved from the Enron repository is still in its raw, but mostly clean and filtered form. This means the dataset is unstructured and unfocused for the tasks we are solving for. Since our goals are to classify the email contents to determine overall company sentiment (negative/positive) and alignment with company objectives, I'll need to transform the unstructured texts into a supervised dataset that we will use to train a recurrent network.
In an increasingly competitive world, we should have a deep understanding of the business in which we operate, how it is evolving, and the new innovations that we could embrace or build to remain competitive and conquer new market segments. To do this, we must be able to develop a clear vision of transformation that takes us to another level of performance. By embracing Digital Transformation, we will deal with artificial intelligence, machine and deep learning, virtual reality, and a lot of other innovative technologies. At first sight, it might even sound fearful to lead the business in such a complex and intricate direction. With this in mind, we will consider some strategies to better understand and take competitive advantage of the huge streaming of data in the current era of the digital revolution.
One mark of a successful data scientist is the desire to continue to learn and grow as new innovations, applications, and technologies are developed. At ODSC West 2021 this November 16th-18th, we'll have 80 training sessions and workshops on essential tools and languages led by some of the best and brightest minds in data science and AI. With options for both in-person and virtual tickets, there's a way for anyone to get the training they need. Here's a sneak peek at top ODSC West training sessions and workshops that cover our key focus areas like MLOps, NLP, and machine and deep learning. MLOps & Data Engineering are trending in 2021 as more companies move to operationalize machine learning and integrate with data engineering. NLP research breakthroughs accelerated in 2019 and 2020 and we expect to host many sessions on topics such as pre-trained NLP models, transfer learning, and transformers.
Applying artificial intelligence to big data can predict – and prevent – crime. When a social media site throws out an ad for a product you were just discussing over the phone, it's easy to jump to conclusions: They must be listening, surely. But the truth is that the site employed artificial intelligence (AI) to predict your behaviour. You searched for a yeast starter last week and commented on a friend's photo of sourdough bread yesterday. The ad for a bread-making course that seemingly pops up out of the blue was shown to you because the data predicted you might be interested in it – based on your own and previous users' behaviour.
About Hipcamp Hipcamp unlocks access to private land, creating new places for people to get outside and go camping, glamping, or RV'ing. We believe that spending time in nature is essential to a happy and healthy human life, and we are deeply passionate about our mission to get more people outside. We are proud of the impact Hipcamp creates by making nature more accessible, providing income to support the protection of private land, and creating community across the urban rural divide. Hipcamp's mission is to connect people with the magic of the outdoors. We make Hipcamp successful by understanding our users and inspiring them to engage with our platform.
There is only one Data Cloud. Snowflake's founders started from scratch and designed a data platform built for the cloud that is effective, affordable, and accessible to all data users. They engineered Snowflake to power the Data Cloud, where thousands of organizations unlock the value of their data with near-unlimited scale, concurrency, and performance. This is our vision: a world with endless insights to tackle the challenges and opportunities of today and reveal the possibilities of tomorrow. Snowfake's future success depends upon making our users: data scientists, app developers, and data engineers successful.
CentralReach is a leading provider of end-to-end EMR, practice management and clinical solutions that enable applied behavior analysis (ABA) clinicians and educators to produce superior outcomes for people with autism. The company is revolutionizing the ABA space with cutting-edge solutions including precision teaching, clinical data collection, scheduling, billing, learning management, fully digital evidence-based programming and more. Trusted by more than 100,000 clinicians and educators, CentralReach is committed to ongoing product improvement, market-leading industry expertise, world-class client satisfaction, and support of the ABA community to propel industry practitioners into a new era of excellence. This position will report to the Director, Onboarding and be a part of the professional services division. The Data Analyst will work with the CentralReach onboarding, customer success and customer themselves to develop custom reports and dashboards using our integrated business intelligence tools.