Smart Data Webinar: Machine Learning Update from DATAVERSITY To view the On Demand recording from the webinar, click HERE>> About the Webinar Machine Learning (ML) approaches and their supporting technologies can generally be classified as Supervised vs Unsupervised, and within those categories as General or Deep Learning (with Reinforcement Learning as a special case within [?]
To view just the slides from the webinar, click HERE>> About the Webinar Machine Learning (ML) approaches and their supporting technologies can generally be classified as Supervised vs Unsupervised, and within those categories as General or Deep Learning (with Reinforcement Learning as a special case within Supervised Learning). The approaches may be based on biological [?]
Click to learn more about author Kimberly Nevala. Despite the amazing potential of Artificial Intelligence (AI), there are some things it just won?t do. If not properly addressed, these considerations can become immovable barriers to AI adoption. As you may already suspect, they have very little to do with the technology itself or the availability [?]
by Angela Guess A recent press release reports, ?Qubole, the cloud big data-as-a-service company, and Snowflake Computing, the only data warehouse built for the cloud, today announced a new partnership that enables organizations to use Apache Spark in Qubole with data stored in Snowflake. With the new integration between cloud services, data teams are able [?]
Artificial Intelligence (AI) and Machine Learning(ML) are jointly contributing to the gradual build-up of the ?Intelligent Digital Mesh? so candidly described in Gartner?s Top 10 Strategic Technology Trends for 2018. Artificial Intelligence and Machine Learning have been forecasted to be the game-changers of the coming decade. Most of the tech trends discussed really fall under [?]
Artificial Intelligence (AI) and Machine Learning are projected to become mainstream technologies in the coming years, and are clearly already having a significant impact across many industries. How exactly is this happening? How are Data Scientists using their skills to develop better Machine Learning algorithms? Where are these innovative technologies going in the future? With [?]
by Angela Guess According to a recent press release, ?Trifacta, a global leader in data wrangling, today announced expanded support for Amazon Web Services (AWS) and the availability of Wrangler Edge and Wrangler Enterprise on AWS Marketplace, allowing organizations to deploy Trifacta in less than an hour. Trifacta has also earned AWS Machine Learning (ML) [?]
by Angela Guess According to a recent press release, ?Amazon Web Services, Inc., an Amazon.com company, announced the Amazon ML Solutions Lab, a new program that connects machine learning experts from across Amazon with AWS customers to help identify practical uses of machine learning inside customers? businesses, and guide them in developing new machine learning-enabled [?]
Machine Learning (ML) ??explores the construction and study of learning algorithms.? (DAMA DMBOK). Furthermore, Machine Learning: ??is about building programs with adaptable parameters that automatically adjust based on the data the programs receive. By adapting to previously seen data, the programs are able to improve their behavior. They also generalize data, meaning that the programs [?]
Click to learn more about author Alejandro Correa Bahnsen. Almost everyone has heard the words ?Machine Learning?, but most people don?t fully understand what they mean. Machine Learning isn?t a single formula that is simply applied to a problem. There are many algorithms to choose from, each of which can be used to achieve different [?]
by Angela Guess According to a new press release, ?Databricks, provider of the leading Unified Analytics Platform and founded by the team who created Apache Spark?, today announced the opening of its new EMEA headquarters in London to support the company?s international growth. As part of this, Databricks has appointed David Wyatt, who built MuleSoft?s [?]
One of biggest challenges facing enterprises today is Data Security and Data Privacy. The emergence of potent data technologies such as Big Data, Machine Learning (ML), and the Internet of Things (IoT) in the Data Management landscape has now sparked a new interest in Data Governance. With so much multi-channel data flowing into an average [?]
by Angela Guess According to a new press release, ?Cloudian, the innovation leader in enterprise object storage systems, has teamed with Skymind Inc., the creator of the Deeplearning4j open-source deep-learning library, to create data management solutions for the hyper-scalable data sets necessary for artificial intelligence (AI) and machine learning (ML) use cases. Under the partnership, [?]
Machine Learning (ML) has transformed traditional computing by enabling machines to learn from data. Machine Learning algorithms have built-in smarts to use available data to answer questions. Apart from using data to learn, ML algorithms can also detect patterns to uncover anomalies and provide solutions. Insecurity environments, Machine Learning can move one step ahead of [?]
If you?re a programmer, your nervous system will scream for anything that can relieve the Programming an information system can be strenuous labor. If you?ve ever spent hours intently producing some intricately detailed textual composition, you know what I mean. And if you?re typing out mind-nu
In mammals, the Y chromosome strictly influences the maintenance of male germ cells. Almost all mammalian species require genetic contributors to generate testes. An endangered species, Tokudaia osimensis , has a unique sex chromosome composition XO/XO, and genetic differences between males and females have not been confirmed. Although a distinctive sex-determining mechanism may exist in T. osimensis , it has been difficult to examine thoroughly in this rare animal species. To elucidate the discriminative sex-determining mechanism in T. osimensis and to find a strategy to prevent its possible extinction, we have established induced pluripotent stem cells (iPSCs) and derived interspecific chimeras using mice as the hosts and recipients. Generated iPSCs are considered to be in the so-called ?true naïve? state, and T. osimensis iPSCs may contribute as interspecific chimeras to several different tissues and cells in live animals. Surprisingly, female T. osimensis iPSCs not only contributed to the female germ line in the interspecific mouse ovary but also differentiated into spermatocytes and spermatids that survived in the adult interspecific mouse testes. Thus, T. osimensis cells have high sexual plasticity through which female somatic cells can be converted to male germline cells. These findings suggest flexibility in T. osimensis cells, which can adapt their germ cell sex to the gonadal niche. The probable reduction of the extinction risk of an endangered species through the use of iPSCs is indicated by this study.
We describe a fast, easy, and potentially universal method for the de novo solution of the crystal structures of membrane proteins via iodide?single-wavelength anomalous diffraction (I-SAD). The potential universality of the method is based on a common feature of membrane proteins?the availability at the hydrophobic-hydrophilic interface of positively charged amino acid residues with which iodide strongly interacts. We demonstrate the solution using I-SAD of four crystal structures representing different classes of membrane proteins, including a human G protein?coupled receptor (GPCR), and we show that I-SAD can be applied using data collection strategies based on either standard or serial x-ray crystallography techniques.
Methylmercury (CH3Hg+) is a potent neurotoxin produced by certain anaerobic microorganisms in natural environments. Although numerous studies have characterized the basis of mercury (Hg) methylation, no studies have examined CH3Hg+ degradation by methanotrophs, despite their ubiquitous presence in the environment. We report that some methanotrophs, such as Methylosinus trichosporium OB3b, can take up and degrade CH3Hg+ rapidly, whereas others, such as Methylococcus capsulatus Bath, can take up but not degrade CH3Hg+. Demethylation by M. trichosporium OB3b increases with increasing CH3Hg+ concentrations but was abolished in mutants deficient in the synthesis of methanobactin, a metal-binding compound used by some methanotrophs, such as M. trichosporium OB3b. Furthermore, addition of methanol (>5 mM) as a competing one-carbon (C1) substrate inhibits demethylation, suggesting that CH3Hg+ degradation by methanotrophs may involve an initial bonding of CH3Hg+ by methanobactin followed by cleavage of the C?Hg bond in CH3Hg+ by the methanol dehydrogenase. This new demethylation pathway by methanotrophs indicates possible broader involvement of C1-metabolizing aerobes in the degradation and cycling of toxic CH3Hg+ in the environment.