Presentation on data preparation with pandasAkshitaKanther
Data preparation is the first step after you get your hands on any kind of dataset. This is the step when you pre-process raw data into a form that can be easily and accurately analyzed. Proper data preparation allows for efficient analysis - it can eliminate errors and inaccuracies that could have occurred during the data gathering process and can thus help in removing some bias resulting from poor data quality. Therefore a lot of an analyst's time is spent on this vital step.
Moving data about library resources among systems often engenders data cleanup processes. What is the best way to clean up data? Which tools and skills for non-programmers can help? See how University of California, Riverside Libraries tackle this issue, then share tips and techniques in an open forum.
Presentation on data preparation with pandasAkshitaKanther
Data preparation is the first step after you get your hands on any kind of dataset. This is the step when you pre-process raw data into a form that can be easily and accurately analyzed. Proper data preparation allows for efficient analysis - it can eliminate errors and inaccuracies that could have occurred during the data gathering process and can thus help in removing some bias resulting from poor data quality. Therefore a lot of an analyst's time is spent on this vital step.
Moving data about library resources among systems often engenders data cleanup processes. What is the best way to clean up data? Which tools and skills for non-programmers can help? See how University of California, Riverside Libraries tackle this issue, then share tips and techniques in an open forum.
Redis project : Relational Databases to Key-Value systemsLamprini Koutsokera
Avaliable at: https://github.com/dbsmasters/bdsmasters
The current project is implemented in the context of the course "Big Data Management Systems" taught by Prof. Chatziantoniou in the Department of Management Science and Technology (AUEB). The aim of the project is to familiarize the students with big data management systems such as Hadoop, Redis, MongoDB and Azure Stream Analytics.
Basically, I don't give any description but I want to tell you that I made this PPT with my crush. That's why it is my first PPT which I can upload on slide share.
Graphs and Artificial Intelligence have long been a focus for Franz Inc. and currently we are collaborating with Montefiore Health System, Intel, Cloudera, and Cisco to improve a patient’s ability to understand the probabilities of their future health status. By combining artificial intelligence, semantic technologies, big data, graph databases and dynamic visualizations we are deploying a Cognitive Probability Graph concept as a means to help predict future medical events.
The power of Cognitive Probability Graphs stems from the capability to combine the probability space (statistical patient data) with a knowledge base of comprehensive medical codes and a unified terminology system. Cognitive Probability Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of machine learning, semantics, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence.
We believe this approach will be transformative for the healthcare field and we see numerous possibilities that exist across business verticals.
During the presentation we will describe the Cognitive Probability Graph concepts using a distributed graph database on top of Hadoop along with the query language SPARQL to extract feature vectors out of the data, applying R and SPARK ML, and then returning the results for further graph processing. #AllegroGraph
This introduction show how OpenRefine can help any data project, from analytics, migration or reconciliation. OpenRefine powerful interface helps domains expert to explore, transform and enrich their data.
Big Data LDN 2018: TIPS AND TRICKS TO WRANGLE BIG, DIRTY DATAMatt Stubbs
Date: 14th November 2018
Location: Data Ops Theatre
Time: 11:50 - 12:20
Speaker: Marion Azoulai
Organisation: TIBCO
About: Data science may be “one of the sexiest jobs of the 21st Century,” but it’s likely your most valuable analytics employees are spending too much time on the most mundane tasks: prepping data for analysis. Make it easy to clean and work with data to give time back to your analytics talent so they can focus on answering questions, solving problems, and discovering opportunities to innovate. Join this session to learn practical tips and tricks to significantly reduce the time needed to transform and wrangle data and leave more time for generating insights.
ComputableFacts: a Secure System to Store Documents and GraphsAccumulo Summit
This 20 minutes talk describes an automated data processing system, ComputableFacts, whose goal is to recover information from unstructured data in a variety of formats (such as Microsoft Office or Adobe PDF documents, emails, web pages, etc.) and convert it into a more usable form. Its key features are :
Security:
• Enforce authorizations across multiple access models to the database: batch, interactive and real-time.
Data Engineering:
• Extract data and metadata from a variety of sources and file formats
• Provides a uniform representation of all data, regardless of its initial structure or format.
Knowledge Engineering:
• Build facts databases manually and/or automatically
• Automatically derive new facts using rules
• Execute complex queries
Knowledge Dissemination:
• Allow users to create alerts
• Allow users to share and comment on documents
• Allow users to create and export query-focused datasets
• Allow users to rate documents. Later, recommend them documents of interest.
Redis project : Relational Databases to Key-Value systemsLamprini Koutsokera
Avaliable at: https://github.com/dbsmasters/bdsmasters
The current project is implemented in the context of the course "Big Data Management Systems" taught by Prof. Chatziantoniou in the Department of Management Science and Technology (AUEB). The aim of the project is to familiarize the students with big data management systems such as Hadoop, Redis, MongoDB and Azure Stream Analytics.
Basically, I don't give any description but I want to tell you that I made this PPT with my crush. That's why it is my first PPT which I can upload on slide share.
Graphs and Artificial Intelligence have long been a focus for Franz Inc. and currently we are collaborating with Montefiore Health System, Intel, Cloudera, and Cisco to improve a patient’s ability to understand the probabilities of their future health status. By combining artificial intelligence, semantic technologies, big data, graph databases and dynamic visualizations we are deploying a Cognitive Probability Graph concept as a means to help predict future medical events.
The power of Cognitive Probability Graphs stems from the capability to combine the probability space (statistical patient data) with a knowledge base of comprehensive medical codes and a unified terminology system. Cognitive Probability Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of machine learning, semantics, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence.
We believe this approach will be transformative for the healthcare field and we see numerous possibilities that exist across business verticals.
During the presentation we will describe the Cognitive Probability Graph concepts using a distributed graph database on top of Hadoop along with the query language SPARQL to extract feature vectors out of the data, applying R and SPARK ML, and then returning the results for further graph processing. #AllegroGraph
This introduction show how OpenRefine can help any data project, from analytics, migration or reconciliation. OpenRefine powerful interface helps domains expert to explore, transform and enrich their data.
Big Data LDN 2018: TIPS AND TRICKS TO WRANGLE BIG, DIRTY DATAMatt Stubbs
Date: 14th November 2018
Location: Data Ops Theatre
Time: 11:50 - 12:20
Speaker: Marion Azoulai
Organisation: TIBCO
About: Data science may be “one of the sexiest jobs of the 21st Century,” but it’s likely your most valuable analytics employees are spending too much time on the most mundane tasks: prepping data for analysis. Make it easy to clean and work with data to give time back to your analytics talent so they can focus on answering questions, solving problems, and discovering opportunities to innovate. Join this session to learn practical tips and tricks to significantly reduce the time needed to transform and wrangle data and leave more time for generating insights.
ComputableFacts: a Secure System to Store Documents and GraphsAccumulo Summit
This 20 minutes talk describes an automated data processing system, ComputableFacts, whose goal is to recover information from unstructured data in a variety of formats (such as Microsoft Office or Adobe PDF documents, emails, web pages, etc.) and convert it into a more usable form. Its key features are :
Security:
• Enforce authorizations across multiple access models to the database: batch, interactive and real-time.
Data Engineering:
• Extract data and metadata from a variety of sources and file formats
• Provides a uniform representation of all data, regardless of its initial structure or format.
Knowledge Engineering:
• Build facts databases manually and/or automatically
• Automatically derive new facts using rules
• Execute complex queries
Knowledge Dissemination:
• Allow users to create alerts
• Allow users to share and comment on documents
• Allow users to create and export query-focused datasets
• Allow users to rate documents. Later, recommend them documents of interest.
esProc is a software for data computing, query and integration within or between sql based database, data warehouse,hadoop, NoSql DB, local file, network file, excel or access. It is widely used in data migration, ETL tasks, complex event programming, big data, database parallel computing, hadoop and report development.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
2. 9/27/2018 2
Dr.AtifShahzad
WhatW have seen
Logic
Logical variables
Conditional, Negation, Contrapositive,Biconditional
AND, OR,NOT,XOR
Logic gates
TruthTables
BooleanAlgebra
Examples
Q&A
MicrosoftVisio
Microsoft Project
Spreadsheet Concepts:
Using Microsoft Excel
Creating Charts in Microsoft Excel
Debugging Concepts Using Microsoft Excel
Presentation Concepts Using Microsoft PowerPoint
Image Concepts
Memory
Memory Cell
CPU
Register
Program Counter
Fetch-Execute Cycle
Q&A
File Management
Word Processing Basics Using MicrosoftWord
MicrosoftWord Layout and Graphics Features
Making and using compressed Files
WinZip, 7Zip
Notepad++
Wordpad
Adobe acrobat
Sumatra PDF
MathType
8. Database Management System
(DBMS)
9/27/2018
Dr.AtifShahzad
8
collection of
software facilitating
the definition,
construction and
manipulation of
databases
Definition
•record structure
•data elements
•names
•data types
•constraints
etc
Construction
•create database
files
•populate the
database with
records
Manipulation
•querying
•updating
10. Sample
9/27/2018
Dr.AtifShahzad
10
Sample database
Student Name StNo Class Major
Smith 17 1 CS
Brown 8 2 CS
Course CName Cno CrHrs Dept
Database 8803 3 CS
C 2606 3 CS
Section SId CNo Semester Yr Instructor
32 8803 Spring 2000 Smith
25 8803 Winter 2000 Smith
43 2606 Spring 2000 Jones
Grades StNo Sid Grade
17 25 A
17 43 B
file1file2
file3
file4
17. Fields
Hold an individual piece of data
Are named descriptively
Often called a column
Phone book examples
Name, address, e-mail, phone number
Fields may contain no data
9/27/2018
Dr.AtifShahzad
17
18. Data types inTable Fields
9/27/2018
Dr.AtifShahzad
18
• Use for text or combinations of text and numbers, such as addresses, or for numbers that do not require calculations,
such as phone numbers or postal codes (255 characters)Text
• Use for lengthy text and numbers, such as notes. Stores up to 63,999 characters
Memo
• Use for data to be included in mathematical calculations, except money
Number
• Use for dates and times
Date/Time
• Use for currency values and to prevent rounding off during calculations.
Currency
• Use for unique sequential that are automatically inserted with a new record
AutoNumber
• Use for data that can be only one of two possible values, such as Yes/No, True/False, On/Off.
Yes/No
• Use for OLE objects (such as Microsoft Word documents, Microsoft Excel spreadsheets, pictures, sounds,
OLE Object
• Use for hyperlinks (hyperlink: Colored and underlined text or a graphic that you click to go to a file, a location in a file,
a Web page on the World Wide Web, or a Web page on an intranet. Stores up to 2048 characters.Hyperlink
• Use to create a field that allows you to choose a value from another table or from a list of values using a combo box
LookupWizard
19. Records
One full set of fields
Often called a row
Phone book example
Smith, Joe, 123 Some Street, 412-555-
7777
Databases may have unlimited rows
9/27/2018
Dr.AtifShahzad
19
20. Flat-file database
Typically has only one table
If multiple, each has a separate file
Useful for simple data storage needs
Hard to manage large data needs
Can waste disk space
9/27/2018
Dr.AtifShahzad
20
21. Relational database
Made of two or more tables
Tables are related by a common field
Called a relationship or join
Can help organize data
Most common form of database
Maintaining data is easier than flat-file
No wasted disk space
9/27/2018
Dr.AtifShahzad
21
23. Working with a Database
Creating tables
List the necessary fields
Steps to define a field
Descriptively name the field
Specify the field type
Determine the field size
24. 11A-24
Working with a Database
Field types
Describes the type of data stored
Most DBMS use the same types
Text fields store letters and numbers
Numeric field store numbers
Date and time field
Logical field stores yes or no
Binary field stores images or sounds
Counter field generates sequential numbers
Memo fields store large amounts of data
25. 11A-25
Working with a Database
Entering data into a table
Users type data into a field
Data must be entered accurately
Constraints help to verify data
Forms are typically used for data entry
26. 11A-26
Working with a Database
Viewing records
Datasheet view shows all records
Filters can limit the records shown
Display only records matching a criteria
Forms allow viewing one record
27. 11A-27
Working with a Database
Sorting records
Order records based on a field
Multiple sub sorts resolve‘ties’
Several types of sorts
Alphabetic
Numeric
Chronological
Ascending
Descending
28. 11A-28
Working with a Database
Querying a database
Statement that describes desired data
List of fields can be modified
Uses of querying
Find data
Calculate values per record
Delete records
Most important DBMS skill
29. 11A-29
Working with a Database
Query languages
All DBMS use a query language
Most DBMS modify the language
Structured Query Language (SQL)
Most common query language
xBase
Query language for dBase systems
Query by example (QBE)
Interface to SQL or xBase
Interactive query design
30. 11A-30
Query Examples
SQL
Select FirstName, LastName, Phone
From tblPhoneNumbers
Where LastName=“Norton”;
xBase
Use tblPhoneNumbers
List FirstName, LastName, Phone
For LastName=“Norton”
31. 11A-31
Working with a Database
Generating reports
Printed information extracted from
a database
Can calculate data
Calculate data per row
Calculate for entire table
Pictures and formatting can be included