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C2020-010 exam Dumps Source : IBM SPSS Modeler Professional v2

Test Code : C2020-010
Test denomination : IBM SPSS Modeler Professional v2
Vendor denomination : IBM
: 55 real Questions

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IBM IBM SPSS Modeler Professional

a glance at the IBM SPSS Modeler and IBM SPSS records analytics tools | killexams.com real Questions and Pass4sure dumps

IBM's SPSS predictive analytics tools embrace IBM SPSS Modeler and IBM SPSS statistics. SPSS Modeler offers information mining and text analysis utility, while SPSS information is an built-in family unit of products. both tools permit clients to build predictive models and execute other analytics projects.

The IBM SPSS Modeler ambitions clients who fill itsy-bitsy or no programming potential. clients are provided with a drag-and-drop consumer interface, enabling them to build predictive models and operate different records analytics. Modeler can succeed different techniques and algorithms to support the consumer determine assistance hidden within the records. The tool can additionally support in integrating and consolidating every benevolent of data units from dispersed data sources across the organization.

The IBM SPSS data suite is an integrated set of items geared towards extra professional records analysts. SPSS facts addresses the finished analytical technique, from planning to facts assortment, analysis, reporting and deployment.

IBM SPSS Modeler elements

edition 18 offers prerogative here aspects:

  • greater than 30 foundation laptop learning algorithms.
  • Extensions that give endured advancements to live used with open source products, equivalent to R and Python.
  • greater assist for a pair of multithreaded analytical algorithms, together with Random timber, Tree-AS, Generalized Linear Engine, Linear-AS, Linear sheperd Vector laptop and Two-Step-AS clustering.
  • The capacity to rush loads of Python and Spark computing device researching, in addition to different Python analytics libraries natively in Modeler with out requiring the exercise of the Analytic Server, as was required within the previous version.
  • SPSS Modeler bundles are deployed on premises, and SPSS Modeler Gold is accessible as a cloud providing. The customer entrance stop of SPSS Modeler runs below home windows and macOS, whereas the server component runs on Unix, Linux and home windows.

    IBM SPSS Modeler gives prerogative here editions:

  • SPSS Modeler personal: A single-user desktop product.
  • SPSS Modeler expert: A computer product that works with IBM SPSS Analytic Server, proposing better scalability and efficiency and enabling applications to live used throughout a firm.
  • SPSS Modeler top rate: This edition contains superior algorithms and capabilities, such as textual content analytics, entity analytics and social network analysis, that enhance mannequin accuracy with unstructured data.
  • SPSS Modeler Gold: This edition gives analytical altenative management, collaboration and deployment capabilities. SPSS Modeler Gold is furthermore purchasable as a cloud offering.
  • IBM SPSS statistics points

    SPSS facts edition 24 comprises prerogative here fresh facets:

  • The capacity to entry more than one hundred extensions, enabling users to win odds of free libraries written in R, Python and SPSS syntax.
  • The IBM SPSS Extension Hub to browse, download, update, amass rid of and generally manage extensions.
  • a huge upgrade to the custom Dialog Builder, enabling clients to extra readily build and deploy their personal extensions. Enhancements embrace fresh controls and fresh properties for existing controls and a number of different improvements to the person interface.
  • improvements that allow clients to more quite simply and straight away import and export records into SPPS records.
  • improvements to the custom Tables module, including fresh statistical performance and consumer-requested points.
  • IBM SPSS facts offers the following three variants (every with additional modules):

  • SPSS information typical materiel provide advanced statistical tactics that aid linear and nonlinear statistical fashions, in addition to predictive simulation modeling, which money owed for uncertain inputs, geospatial analytics and customized tables.
  • SPSS facts skilled tools sheperd records preparation, missing values and information validity, decision timber, and forecasting.
  • SPSS statistics premium provides superior analytical suggestions, including structural equation modeling, in-depth sampling assessment and checking out. This bundle additionally contains strategies that goal direct marketing and excessive-end charts and graphs.
  • Pricing for the SPSS Modeler and SPSS records predictive analytics materiel compass depending on the bundle alternate options, the variety of clients and the license duration. SPSS facts is now obtainable as a subscription alternative or a perpetual license. IBM presents free trials of each IBM SPSS Modeler and IBM SPSS records.

    next Steps

    Why the time period unstructured records is a misnomer

    How Big statistics is altering facts modeling innovations

    big facts programs pose fresh challenges to information governance

    connected substances View extra

    IBM Watson Studio: Product Overview and perception | killexams.com real Questions and Pass4sure dumps

    download the authoritative guide: Cloud Computing 2019: the usage of the Cloud for aggressive knowledge

    See the entire record of desktop researching SolutionsSee consumer reviews of IBM Watson Studio

    bottom line

    Watson is an umbrella for any IBM profound getting to know and synthetic intelligence, in addition to computer studying. The trade become a pioneer in introducing AI technologies to the company world. What this means for patrons: Watson Studio is a properly contender for any organization trying to installation laptop discovering and profound gaining erudition of applied sciences.

    The platform offers huge tools and technologies for facts scientists, developers and discipline signify number experts that wish to determine information, build models, and teach and set up computing device discovering fashions at scale. The respond comprises tools to share visualizations and outcomes with others. Watson Studio helps cloud, computing device and endemic deployment frameworks.

    The latter resides at the back of an organization’s firewall or as a SaaS respond running in an IBM private cloud. IBM Watson Studio is ranked as a “chief” within the Forrester Wave. It become a consumers’ alternative 2018 recipient at Gartner Peer Insights.

    Product Description

    Watson Studio relies on a group of IBM tools and technologies to build effective desktop discovering purposes and features. This contains IBM Cloud pretrained computing device learning models comparable to visible recognition, Watson natural Language Classifier, and others. The environment makes exercise of Jupyter Notebooks together with other open supply tools and scripting languages to enrich constructed-in collaborative venture aspects.

    https://o1.qnsr.com/log/p.gif?;n=203;c=204660772;s=9478;x=7936;f=201812281334210;u=j;z=TIMESTAMP;a=20403954;e=i

    The outcomes is an ambiance that facilitates quick and powerful computer getting to know structure and best tuning of models. records scientists and others can execute a altenative from a variety of capacities of Anaconda, Spark and GPU environments.

    Watson Studio helps more advantageous visual modeling via a drag-and-drop interface offered by using IBM’s SPSS Modeler. furthermore, it contains computerized profound discovering the exercise of a drag-and-drop, no-code interface in Neural network Modeler.

    Overview and lines consumer Base

    facts scientists, builders and subject matter experts.

    Interface

    Graphical drag-and-drop and command line.

    Scripting Languages/codecs Supported

    helps Anaconda and Apache Spark. The latter presents Scala, Python and R interfaces.

    formats Supported

    Most most Important records and file formats are supported via open supply Jupyter Notebooks.

    Integration

    IBM Watson Studio connects a number of IBM items, including SPSS Modeler and records Science event (DSX) together with open supply equipment, with the end to convey a strong Predictive Analytics and computing device discovering (PAML) solution.

    The environment accommodates open statistics sets via Jupyter Notebooks, Apache Spark and the Python Pixiedust library. The cloud version points interactivity with notebook servers and R Studio, together with Python, R., and Scala coder for statistics scientists.

    Reporting and Visualization

    Visualization through SPSS Modeler. potent logging and reporting functions are developed into the product.

    Pricing

    IBM has adopted a pay-as-you-go model. Watson Studio Cloud – generic prices $ninety nine per 30 days with 50 talent unit hours per thirty days included. Watson Studio Cloud - enterprise runs $6,000 per thirty days with 5,000 capability unit hours. Watson Studio laptop prices $199 monthly with limitless modeling. Watson Studio endemic – for trade information science teams N/A.

    IBM Watson Studio Overview and contours at a glance:

    dealer and features

    IBM Watson Studio

    ML focal point

    broad facts science focus with cloud and laptop ML platforms.

    Key aspects and capabilities

    amazing visible attention and herbal classification equipment. springy strategy that accommodates open supply tools. Connects to IBM SPSS Modeler.

    person comments

    incredibly rated for features and capabilities. Some complaints revolving round the exercise of notebooks.

    Pricing and licensing

    Tiered model from $99 monthly per person to $6,000 monthly per user or extra at enterprise degree.


    IBM sends Cognos, SPSS to the cloud | killexams.com real Questions and Pass4sure dumps

    Two of IBM’s most universal analysis items, the Cognos trade Intelligence and the SPSS predictive analytics package, are headed for the cloud, the latest in an ongoing shove by IBM to port its giant utility portfolio to the cloud.

    accessing this type of software from a hosted environment, in preference to deciding to buy the package outright, gives a few merits to purchasers.

    “We manage the infrastructure, and this means that you can scale greater conveniently and amass began with much less upfront funding,” spoke of Eric Sall, IBM vice president of international analytics advertising.

    IBM announced these additions to its cloud functions, as well as a few fresh choices, at its perception user conference for information analytics, held this week in Las Vegas.

    via 2016, 25 % of recent company evaluation deployments will live achieved within the cloud, according to Gartner.

    Analytics could support organizations in lots of ways, according to IBM. It could give extra perception within the buying habits of valued clientele, as well as perception into how smartly its personal operations are performing. It could support win trust of programs from assaults and makes an attempt at fraud, as well as assure that trade departments are meeting compliance requirements.

    the fresh online edition of Cognos, IBM Cognos enterprise Intelligence on Cloud, can currently live confirmed in a preview mode. IBM plans to present Cognos as a plenary trade provider early next 12 months. clients can rush Cognos against records they preserve in the IBM cloud, or towards data they reclaim on premises.

    A plenary industrial edition of the on-line IBM SPSS Modeler may live obtainable within 30 days. This materiel will consist of any of the SPSS add-ons for data based mostly predictive modeling, such as a modeler server, analytics altenative management application and a facts server.

    past this yr, IBM pledged to present a whole lot of its utility portfolio as cloud functions, many via its Bluemix set of platform functions.

    moreover Cognos and SPSS, IBM additionally unveiled a few fresh and up to date offerings on the convention.

    One fresh service, DataWorks, gives a few concepts for refining and cleansing information so it is capable for analysis. The trade has launched a cloud-based facts warehousing service, called dashDB. a fresh Watson-primarily based service, referred to as Watson Explorer, offers a way for users to question natural language questions about assorted units of inner data.

    To observation on this text and other PCWorld content, talk over with their fb web page or their Twitter feed.

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    IBM SPSS Modeler Professional v2

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    A view at the IBM SPSS Modeler and IBM SPSS Statistics analytics tools | killexams.com real questions and Pass4sure dumps

    IBM's SPSS predictive analytics tools consist of IBM SPSS Modeler and IBM SPSS Statistics. SPSS Modeler provides data mining and text analysis software, while SPSS Statistics is an integrated family of products. Both tools enable users to build predictive models and execute other analytics tasks.

    The IBM SPSS Modeler targets users who fill itsy-bitsy or no programming skills. Users are provided with a drag-and-drop user interface, enabling them to build predictive models and execute other data analytics. Modeler can apply different processes and algorithms to support the user determine information hidden in the data. The tool can furthermore assist in integrating and consolidating any types of data sets from dispersed data sources across the organization.

    The IBM SPSS Statistics suite is an integrated set of products geared toward more professional data analysts. SPSS Statistics addresses the complete analytical process, from planning to data collection, analysis, reporting and deployment.

    IBM SPSS Modeler features

    Version 18 provides the following features:

  • More than 30 foundation machine learning algorithms.
  • Extensions that provide continued improvements for exercise with open source products, such as R and Python.
  • Enhanced support for several multithreaded analytical algorithms, including Random Trees, Tree-AS, Generalized Linear Engine, Linear-AS, Linear Support Vector Machine and Two-Step-AS clustering.
  • The talent to rush a variety of Python and Spark machine learning, as well as other Python analytics libraries natively in Modeler without requiring the exercise of the Analytic Server, as was required in the previous version.
  • SPSS Modeler bundles are deployed on premises, and SPSS Modeler Gold is available as a cloud offering. The client front stop of SPSS Modeler runs under Windows and macOS, while the server component runs on Unix, Linux and Windows.

    IBM SPSS Modeler provides the following editions:

  • SPSS Modeler Personal: A single-user desktop product.
  • SPSS Modeler Professional: A desktop product that works with IBM SPSS Analytic Server, providing improved scalability and performance and enabling applications to live used across an organization.
  • SPSS Modeler Premium: This edition includes advanced algorithms and capabilities, such as text analytics, entity analytics and social network analysis, that multiply model accuracy with unstructured data.
  • SPSS Modeler Gold: This edition provides analytical decision management, collaboration and deployment capabilities. SPSS Modeler Gold is furthermore available as a cloud offering.
  • IBM SPSS Statistics features

    SPSS Statistics version 24 includes the following fresh features:

  • The talent to access more than 100 extensions, enabling users to win odds of free libraries written in R, Python and SPSS syntax.
  • The IBM SPSS Extension Hub to browse, download, update, remove and generally manage extensions.
  • A major upgrade to the Custom Dialog Builder, enabling users to more easily build and install their own extensions. Enhancements embrace fresh controls and fresh properties for existing controls and several other improvements to the user interface.
  • Improvements that enable users to more easily and quickly import and export data into SPPS Statistics.
  • Improvements to the Custom Tables module, including fresh statistical functionality and customer-requested features.
  • IBM SPSS Statistics offers the following three editions (each with additional modules):

  • SPSS Statistics Standard tools provide advanced statistical procedures that support linear and nonlinear statistical models, as well as predictive simulation modeling, which accounts for uncertain inputs, geospatial analytics and customized tables.
  • SPSS Statistics Professional tools support data preparation, missing values and data validity, decision trees, and forecasting.
  • SPSS Statistics Premium adds advanced analytical techniques, including structural equation modeling, in-depth sampling assessment and testing. This bundle furthermore includes procedures that target direct marketing and high-end charts and graphs.
  • Pricing for the SPSS Modeler and SPSS Statistics predictive analytics tools vary depending on the bundle options, the number of users and the license period. SPSS Statistics is now available as a subscription option or a perpetual license. IBM offers free trials of both IBM SPSS Modeler and IBM SPSS Statistics.

    Next Steps

    Why the term unstructured data is a misnomer

    How Big data is changing data modeling techniques

    Big data systems pose fresh challenges to data governance

    Related Resources View More

    A simple Play On Self-Service Big Data Prep And Analytics: Wait For Smarter Valuation Entry Point | killexams.com real questions and Pass4sure dumps

    No result found, try fresh keyword!According to Rexer Analytics, 2016 Data Science Survey of 1220 analytics professionals from 72 countries, the tolerable analytics professional reports ... s end-to-end data science platform; IBM’s (NYSE ...

    Genetic map construction and QTL analysis of leaf-related traits in soybean under monoculture and relay intercropping | killexams.com real questions and Pass4sure dumps

    Plant materials and experiment design

    The RILs of 200 individuals were developed from a cross between the cultivar ‘Nandou 12’ (female) and the Sichuan local variety ‘Jiuyuehuang’ (male). ‘Nandou 12’ has lodging resistance and strong shade tolerance, which are significantly different from the phenotypic characters of ‘Jiuyuehuang’.

    The field experiments of monoculture and relay intercropping were conducted in the Modern Agricultural foundation of Renshou County, Sichuan Province, China (104°09′N, 30°00′E). In these experiments, 137 F7 RILs and 200 F8 RILs were grown together with two parents in a randomized obstruct design with two replications on June 15, 2015 and 2016, respectively. In monoculture planting, each plot included 25 plants with 0.5 m between rows and 0.1 m between plants. In relay intercropping with a wide-narrow row cropping pattern (two maize rows with a 0.4 m inter-row distance and two soybean rows with a 0.5 m inter-row distance), adjacent rows of maize and soybean spaced 0.55 m, and 0.16 m and 0.1 m between plants of maize and soybean, respectively. The row length was 2.5 m. ‘Zhenghong 505’ (Zea mays L.) as the semi-compact maize was cultivated in narrow rows on April 1, 2015 and 2016, and harvested on August 5, 2015 and 2016. The soybean was cultivated in wide rows, and the other conditions were the very as those of the monoculture.

    According to the field experiment phenotype data, two parents, RIL64 (weaker shade tolerance), and RIL87 (stronger shade tolerance) were analyzed to gene expression by real-time PCR. The above four accessions were sowed under daily light (CK, PPFD = 878.15 μmol/m2/s), one layer of black sun-shade net (T1, PPFD = 336.79 μmol/m2/s), and two layers of black sun-shade net (T2, PPFD = 251.54 μmol/m2/s) with three repeats.

    Measurement of leaf-related traits

    The soybean samples in field were collected 40 days after germination. Three daily samples with two repeats of each parent and RIL individual were selected to determine their leaf-related phenotype data. The following standards were used to evaluate the six leaf-related traits: CLN; TLA, which exercise the pocket puncher amass the round piece (diameter = 1.2 cm), then divide the pocket locality by the round piece weight and multiply by the total leaf desiccate weight; SLA, which is the ratio of the locality of one side of a small round leaf piece to its desiccate weight; SLW, which is the reciprocal of SLA; LDW; and LDWR, which is the ratio of LDW to the sum of LDW and stem petiole desiccate weight.

    ‘Nandou 12’, ‘Jiuyuehuang’, RIL64, and RIL87 for candidate gene analysis were sampled to measure TLA, SLA, LDW, and SLW. The fully developed unifoliate leaves, unrolling first trifoliate leaves, and unrolling second trifoliate leaves were collected in 7 days (V0), 15 days (V1), and 23 days (V2) after germination under three treatments with repeated three times, respectively.

    DNA extraction

    The young leaves of 2 parents and 200 individuals of RILs were collected 20 days after germination. DNA was extracted as described by Doyle and Doyle31 with slight modifications. In brief, 3–5 g of fresh leaves were grinded and powdered in a mortar with liquid nitrogen and placed in a pre-cooled 2 mL Eppendorf tube (load 1/3), then mixed into 65 °C 600 μL of preheated CTAB and 20 μL of hydrophobic foundation ethanol, and incubated in a water bath at 65 °C for about 1 h. The preparation was gently shaken once every 10 min. Afterward, 400 μL of Tris-balance phenol and 400 μL of chloroform iso-amyl alcohol solution were added (24:1), fully mixed and gently shaken for 15 min. The samples were centrifuged for 10 min at 10,000 rpm. Then, 500 μL of the supernatant was transferred into a fresh Eppendorf tube, finished once suction filter with 400 μL of chloroform iso-amyl alcohol solution (24:1). The resulting admixture was centrifuged at 10,000 rpm for 10 min, and 400 μL of the supernatants was transferred into a fresh Eppendorf tube and added with 1 mL of pre-cooled isopropyl alcohol. The admixture was blended gently until the flocculent precipitated completely. The flocculent was gently selected from the admixture by using a syringe, transferred into a fresh Eppendorf tube, washed twice with 70% ethanol, then washed with anhydrous ethanol, blow dried in a cleanly bench, and dissolved in 200 μL of TE buffer. Finally, NanoVue was used to detect DNA quality, and agarose gel electrophoresis was conducted.

    Genotyping

    The DNA fragments of each parent were randomly sheared into ~500 bp by ultrasonication, and the sequencing library was constructed by stop repair, 3′-plus A, plus sequencing connector, purification, and PCR amplification. The library was sequenced through the HiSeqTM 2500 system (Illunima, USA) sequencing platform after passing attribute inspection. A high-density genetic linkage map for 200 RILs was constructed with a SLAF-seq technology. The SLAF marker was identified and genotyped in accordance with the procedures described by Sun et al.32. The original sequencing of SLAF-seq library was PE125bp. After the raw data were filtered, the reads in the Glycine max genome sequence were compared using the BWA software, and sequences mapped in the very position were defined as one SLAF locus. The alleles of each SLAF locus were then defined in accordance with parental reads with a sequence depth of >15X fold, and each genotype sequence contained 30% of the offspring information. Only SLAFs with two to four alleles were identified as polymorphic and considered potential markers. any polymorphism SLAF loci were genotyped with consistency in parental and offspring SNP loci. The marker codes of the polymorphic SLAFs were analyzed on the basis of the RILs. High-quality SLAF markers for the genetic mapping were filtered to construct the map.

    Genetic map construction

    Genetic map construction was based on 200 F7 RILs and was completed by using HighMap software by Beijing Biomarker Technologies (www.biomarker.com.cn). First, the recombination rate and the modified logarithm of odd (LOD) scores between markers were calculated to infer the linkage phases in chromosomes, through the maximum likelihood way for genetic map construction, according to the map order to rectify and sequence circularly, and a high attribute genetic map was obtained.

    QTL analysis and Go enrichment

    QTL analysis was performed through the inclusive composite interval mapping (ICIM)33 of QTL IciMapping 4.1. An QTL was significant with the LOD score of 2.5. The nomenclature of McCouch et al.34 was used as a reference with slight modifications. The denomination of the QTLs in this study included four parts. For example, q, CLN, 17, and 3 of qCLN17-3 represented QTL, trait abbreviation, chromosome number, and QTL position in this chromosome, respectively. QTL mapping was drawn by MapDraw35. QTL validation was conducted with the software of QTL.gCIMapping.GUI in data of this study (https://cran.r-project.org/web/packages/QTL.gCIMapping.GUI/index.html)36.

    The topGO software was used to conduct enrichment analysis of the related genes between the sample groups annotated into the Go database, and the hierarchical relationship of the nodes significantly enriched in the Go system was demonstrated visually in the configuration of directed acyclic graph.

    RNA extraction, cDNA synthesis and real-time PCR

    The leaves for RNA extraction were sampled with liquid nitrogen frozen in 7 days, 15 days, and 23 days after germination. RNA extraction was conducted according to the Plant RNA Kit (Omega Bio-tek, Inc., USA) instruction. The cDNA synthesis and real-time PCR were conducted according to the RT reagent Kit (Takara Bio, Inc., Japan) and SYBR Premix Ex Taq II (Takara Bio, Inc., Japan) instructions, respectively. Primers were designed by Takara Bio and synthesized by Sangon Biotech (Shanghai, China). Real-time PCR conducted with QuantStudioTM 6 Flex System and calculated the RQ value with 2(−∆∆CT) in Real-Time PCR Software v1.3 (Thermo Fisher, USA).

    Data statistics

    Microsoft surpass 2013 was used for data-calculated analysis and the gene expression profiles. IBM SPSS Statistics 22 was utilized to conduct the ANOVA and correlation analysis of the leaf-related traits. origin Pro 8.0 was employed to draw the histogram.



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