AWS makes it easy to migrate databases to the cloud and then operate them, faster and more cost-effectively. Our database capabilities also enable a number of methods to protect database volumes, and this session will help you understand best practices for backing up database instances in the cloud and then storing them in S3 for durable and available storage.
This presentation was given at the Atlanta Hadoop User Group and outline the architecture a real-time reporting platform we build in 45 days at IgnitionOne.
The session focused on Data Mining using R Language where I analyzed a large volume of text files to find out some meaningful insights using concepts like DocumentTermMatrix and WordCloud.
AWS makes it easy to migrate databases to the cloud and then operate them, faster and more cost-effectively. Our database capabilities also enable a number of methods to protect database volumes, and this session will help you understand best practices for backing up database instances in the cloud and then storing them in S3 for durable and available storage.
This presentation was given at the Atlanta Hadoop User Group and outline the architecture a real-time reporting platform we build in 45 days at IgnitionOne.
The session focused on Data Mining using R Language where I analyzed a large volume of text files to find out some meaningful insights using concepts like DocumentTermMatrix and WordCloud.
Masterclass: Natural Language Processing in Trading with Terry Benzschawel & ...QuantInsti
Terry Benzschawel (Founder and Principal at Benzschawel Scientific, LLC) and Ishan Shah (AVP, Content & Research at QuantInsti) helm this Masterclass about Natural Language Processing in Trading.
In this session, Terry and Ishan discuss:
- How is Natural Language Processing applied in financial markets?
- Calculating Daily Sentiment Score on Quantra learning portal
- Compare different word embedding methods with their pros and cons
- How does Quantra learning portal provide a unique learning experience?
Summary:
This introductory webinar describes the use of Natural Language Processing (NLP) techniques in the context of building trading strategies for 1-day horizons for the corporate bond market and equities markets using news headlines.
We described various methods for converting text into digital representations and for extracting sentiment scores from those embeddings.
Looking ahead to the course, we find that approaches using the latest advances in NLP are better suited to predict future returns in credit indices, by using news headlines directly as inputs, instead of news headline sentiments
About us:
Quantra is an online education portal that specializes in Algorithmic and Quantitative trading. Quantra offers various bite-sized, self-paced and interactive courses that are perfect for busy professionals, seeking implementable knowledge in this domain.
Useful links and some bonus content:
[Blog] Step By Step Guide - http://bit.ly/StepByStepGuideNLP
[Course] Natural Language Processing in Trading - http://bit.ly/QuantraNLPT
[Courses] All Quantra courses - http://bit.ly/AllQuantraCourses
Find more info on - https://quantra.quantinsti.com/
Like us on Facebook: https://www.facebook.com/goquantra/
Follow us on Twitter: https://twitter.com/GoQuantra
Fast and accurate sentiment classification us and naive bayes model b516001Abhisek Sahoo
In today’s world, Social Networking website like Twitter, Facebook , Linkedin, etc. plays a very significant role. Twitter is a micro-blogging platform which provides a tremendous amount of data which can be used for various application of sentiment Analysis like predictions, review, elections, marketing, etc. Sentiment Analysis is a process of extracting information from large amount of data, and classifies them into different classes called sentiments.
Detailed documented with the definition of text mining along with challenges, implementing modeling techniques, word cloud and much more.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Text categorization is a term that has intrigued researchers for quite some time now. It is the concept
in which news articles are categorized into specific groups to cut down efforts put in manually categorizing
news articles into particular groups. A growing number of statistical classification and machine learning
technique have been applied to text categorization. This paper is based on the automatic text categorization
of news articles based on clustering using k-mean algorithm. The goal of this paper is to automatically
categorize news articles into groups. Our paper mostly concentrates on K-mean for clustering and for term
frequency we are going to use TF-IDF dictionary is applied for categorization. This is done using mahaout
as platform.
Data Scientist Salary, Skills, Jobs And Resume | Data Scientist Career | Data...Simplilearn
This presentation about "Data Science Engineer Career, Salary, and Resume" will help you understand who is a Data Science Engineer, the salary of a Data Science Engineer, Data Science Engineer Skillset and Data Science Engineer Resume. Data science is a systematic way to analyze a massive amount of data and extract information from them. Data Science can answer a lot of questions, as well. Data Science is mainly required for
better decision making, predictive analysis, and pattern recognition.
Below are topics that we will be discussing in this presentation:
1. Introduction to Data Science
2. Who is a Data Science Engineer
3. Data Science Engineer Skillset
4. Data Science Engineer job roles
5. Data Science Engineer salary trends
6. Data Science Engineer Resume
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. The data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data, you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package
5. Gain expertise in machine learning using the Scikit-Learn package
Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
Learn more at https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training
APPROACH FOR THICKENING SENTENCE SCORE FOR AUTOMATIC TEXT SUMMARIZATIONIJDKP
In our study we will use approach that combine Natural language processing NLP with Term occurrences to improve the quality of important sentences selection by thickening sentence score along with reducing the number of long sentences that would be included in the final summarization. There are sixteen known methods for automatic text summarization. In our paper we utilized Term frequency approach and built an algorithm to re filter sentences score.
Innovaccer service capabilities with case studiesAbhinav Shashank
Innovaccer is a California based research acceleration firm assisting hundreds of researchers from Harvard, Stanford, Wharton, MIT etc.
This slide describes our capabilities of assisting research endeavors. To get in touch with us, please write to info@innovaccer.com
To know more, please visit our website : www.innovaccer.com
Fundamentals Concepts on Text Analytics.pptxaini658222
Text analytics, also known as text mining, is the process of deriving high-quality information from text sources using software. It is a multidisciplinary field that combines elements of data mining, machine learning, statistics, and natural language processing (NLP) to process and analyze large amounts of natural language data effectively.
This is an introduction to text analytics for advanced business users and IT professionals with limited programming expertise. The presentation will go through different areas of text analytics as well as provide some real work examples that help to make the subject matter a little more relatable. We will cover topics like search engine building, categorization (supervised and unsupervised), clustering, NLP, and social media analysis.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Masterclass: Natural Language Processing in Trading with Terry Benzschawel & ...QuantInsti
Terry Benzschawel (Founder and Principal at Benzschawel Scientific, LLC) and Ishan Shah (AVP, Content & Research at QuantInsti) helm this Masterclass about Natural Language Processing in Trading.
In this session, Terry and Ishan discuss:
- How is Natural Language Processing applied in financial markets?
- Calculating Daily Sentiment Score on Quantra learning portal
- Compare different word embedding methods with their pros and cons
- How does Quantra learning portal provide a unique learning experience?
Summary:
This introductory webinar describes the use of Natural Language Processing (NLP) techniques in the context of building trading strategies for 1-day horizons for the corporate bond market and equities markets using news headlines.
We described various methods for converting text into digital representations and for extracting sentiment scores from those embeddings.
Looking ahead to the course, we find that approaches using the latest advances in NLP are better suited to predict future returns in credit indices, by using news headlines directly as inputs, instead of news headline sentiments
About us:
Quantra is an online education portal that specializes in Algorithmic and Quantitative trading. Quantra offers various bite-sized, self-paced and interactive courses that are perfect for busy professionals, seeking implementable knowledge in this domain.
Useful links and some bonus content:
[Blog] Step By Step Guide - http://bit.ly/StepByStepGuideNLP
[Course] Natural Language Processing in Trading - http://bit.ly/QuantraNLPT
[Courses] All Quantra courses - http://bit.ly/AllQuantraCourses
Find more info on - https://quantra.quantinsti.com/
Like us on Facebook: https://www.facebook.com/goquantra/
Follow us on Twitter: https://twitter.com/GoQuantra
Fast and accurate sentiment classification us and naive bayes model b516001Abhisek Sahoo
In today’s world, Social Networking website like Twitter, Facebook , Linkedin, etc. plays a very significant role. Twitter is a micro-blogging platform which provides a tremendous amount of data which can be used for various application of sentiment Analysis like predictions, review, elections, marketing, etc. Sentiment Analysis is a process of extracting information from large amount of data, and classifies them into different classes called sentiments.
Detailed documented with the definition of text mining along with challenges, implementing modeling techniques, word cloud and much more.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Text categorization is a term that has intrigued researchers for quite some time now. It is the concept
in which news articles are categorized into specific groups to cut down efforts put in manually categorizing
news articles into particular groups. A growing number of statistical classification and machine learning
technique have been applied to text categorization. This paper is based on the automatic text categorization
of news articles based on clustering using k-mean algorithm. The goal of this paper is to automatically
categorize news articles into groups. Our paper mostly concentrates on K-mean for clustering and for term
frequency we are going to use TF-IDF dictionary is applied for categorization. This is done using mahaout
as platform.
Data Scientist Salary, Skills, Jobs And Resume | Data Scientist Career | Data...Simplilearn
This presentation about "Data Science Engineer Career, Salary, and Resume" will help you understand who is a Data Science Engineer, the salary of a Data Science Engineer, Data Science Engineer Skillset and Data Science Engineer Resume. Data science is a systematic way to analyze a massive amount of data and extract information from them. Data Science can answer a lot of questions, as well. Data Science is mainly required for
better decision making, predictive analysis, and pattern recognition.
Below are topics that we will be discussing in this presentation:
1. Introduction to Data Science
2. Who is a Data Science Engineer
3. Data Science Engineer Skillset
4. Data Science Engineer job roles
5. Data Science Engineer salary trends
6. Data Science Engineer Resume
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. The data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data, you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package
5. Gain expertise in machine learning using the Scikit-Learn package
Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
Learn more at https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training
APPROACH FOR THICKENING SENTENCE SCORE FOR AUTOMATIC TEXT SUMMARIZATIONIJDKP
In our study we will use approach that combine Natural language processing NLP with Term occurrences to improve the quality of important sentences selection by thickening sentence score along with reducing the number of long sentences that would be included in the final summarization. There are sixteen known methods for automatic text summarization. In our paper we utilized Term frequency approach and built an algorithm to re filter sentences score.
Innovaccer service capabilities with case studiesAbhinav Shashank
Innovaccer is a California based research acceleration firm assisting hundreds of researchers from Harvard, Stanford, Wharton, MIT etc.
This slide describes our capabilities of assisting research endeavors. To get in touch with us, please write to info@innovaccer.com
To know more, please visit our website : www.innovaccer.com
Fundamentals Concepts on Text Analytics.pptxaini658222
Text analytics, also known as text mining, is the process of deriving high-quality information from text sources using software. It is a multidisciplinary field that combines elements of data mining, machine learning, statistics, and natural language processing (NLP) to process and analyze large amounts of natural language data effectively.
This is an introduction to text analytics for advanced business users and IT professionals with limited programming expertise. The presentation will go through different areas of text analytics as well as provide some real work examples that help to make the subject matter a little more relatable. We will cover topics like search engine building, categorization (supervised and unsupervised), clustering, NLP, and social media analysis.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
3. Manjeet Singh
Information & Data Management Consultant
ASG Group
Information and Data Management Consultant
at ASG Group with more than 15 years'
experience in Information & Data Management
domain.
Experience of working in industries such as
Energy, Oil and Gas, Banking, Local Government
and IT services.
An aspiring Data Scientist and passionate about
Artificial Intelligence (AI) and Machine Learning
(ML).
Place your
photo here
/manjeetsingh-aibipro @manjeetsinghitp
6. Text Analytics / Text Mining
Text Analytics, also known as text mining, is the process of examining
large collections of written resources to generate new information, and to
transform the unstructured text into structured data for use in further
analysis.
7. Text Mining
Extract Documents
1. Text sources such as websites, pdf, DBs
2. Move document text into corpus.
Corpus: Structured set of text annotated with additional
metadata and details.
Transformation
1. Convert to lower case
2. Remove punctuation
3. Remove stop words (e.g. ‘a’, ‘an’, ‘be’ etc)
Extract Features
1. Convert text string into quantifiable measures
2. Count frequency of each term and form a
vector
Perform Analysis (some approaches)
1. Word frequency
2. Document classification
3. Locating specific set of words
etc.
8. Text Mining
Sentiment Analysis is the process of determining
whether a piece of writing is positive, negative or
neutral. It’s also known as opinion mining,
deriving the opinion or attitude of a speaker
https://www.lexalytics.com/technology/sentiment
Sentiment Analysis
9. Text Mining in R
Text mining in R requires following:
Packages
Dataset package
janeaustenr
This package contains the complete text of Jane Austen's 6 completed, published novels,
formatted to be convenient for text analysis
tidyr
Designed for data
tidying
tidytext
It makes text mining
tasks easier, more
effective. Contains
Lexicons
dplyr
a flexible
grammar of
data
manipulation
stringr
Simple, Consistent
Wrappers for
Common String
Operations
ggplot2
Create graphs
Lexicon: The vocabulary of a person, language, or branch of knowledge
10. R in SQL Server
Running ‘R’ code in T-SQL requires either of the following :
SQL Server 2017 Machine
Learning Services, with the R
language installed
SQL Server 2016 R Services Azure Data Science VM
11. DEMO
• Perform Text mining using ‘R’ packages ?
• Run ‘R’ script from with in T-SQL ?