The effort in this webinar is to make the Civil, Mechanical, and Sanitation Engineers understand, that, DSAI is there to make the best use of the understanding of knowledge they have
I am a passionate and hardworking student currently pursuing my Bachelor's degree in Information Technology. My areas of Interest include Software Development, Data Structures and Algorithms, Machine Learning. I am open for full-time Job Opportunities.
I also love creative writing, public speaking, community service and sports.
#OSSPARIS19 - Overcoming open source challenges in reinforcement learning - W...Paris Open Source Summit
#IA Track - Practical applications
Reinforcement learning is a rapidly growing branch of artificial intelligence that has achieved super-human performance in board games such as Go and chess and video games such as Starcraft. Research papers and open code in this field are widely available.
However, unlike other fields of machine learning, open code and research has so far largely failed to translate into real world applications.
In this talk, we leverage the indust.ai team's experience in developing their own reinforcement learning activity to discuss the challenges involved. These include poor reproducibility, varying code quality, prohibitive computation and data requirements, the difference in mindset between traditional machine learning and reinforcement learning, and the difficulty of finding the skills required to transfer academic research to the real world. We will also present some of our approaches for overcoming these issues.
“Semantic PDF Processing & Document Representation”diannepatricia
Sridhar Iyengar, IBM Distinguished Engineer at the IBM T. J. Watson Research Center, presention “Semantic PDF Processing & Document Representation” as part of the Cognitive Systems Institute Group Speaker Series.
The effort in this webinar is to make the Civil, Mechanical, and Sanitation Engineers understand, that, DSAI is there to make the best use of the understanding of knowledge they have
I am a passionate and hardworking student currently pursuing my Bachelor's degree in Information Technology. My areas of Interest include Software Development, Data Structures and Algorithms, Machine Learning. I am open for full-time Job Opportunities.
I also love creative writing, public speaking, community service and sports.
#OSSPARIS19 - Overcoming open source challenges in reinforcement learning - W...Paris Open Source Summit
#IA Track - Practical applications
Reinforcement learning is a rapidly growing branch of artificial intelligence that has achieved super-human performance in board games such as Go and chess and video games such as Starcraft. Research papers and open code in this field are widely available.
However, unlike other fields of machine learning, open code and research has so far largely failed to translate into real world applications.
In this talk, we leverage the indust.ai team's experience in developing their own reinforcement learning activity to discuss the challenges involved. These include poor reproducibility, varying code quality, prohibitive computation and data requirements, the difference in mindset between traditional machine learning and reinforcement learning, and the difficulty of finding the skills required to transfer academic research to the real world. We will also present some of our approaches for overcoming these issues.
“Semantic PDF Processing & Document Representation”diannepatricia
Sridhar Iyengar, IBM Distinguished Engineer at the IBM T. J. Watson Research Center, presention “Semantic PDF Processing & Document Representation” as part of the Cognitive Systems Institute Group Speaker Series.
Artificial Intelligence (AI) is nowadays used frequently in many application domains. Although sometimes considered only as an afterthought in the public discussion compared to other domains such as health, transportation, and manufacturing, the media domain is also transformed by AI enabling new opportunities, from content creation e.g. “robojournalism” and individualised content to optimisation of the content production and distribution. Underlaying many of these new opportunities is the use of AI in its current reincarnation as deep learning for understanding the audio-visual content by extracting structured information from the unstructured data, the audio-visual content.
In this talk the current understanding and trends of AI will therefore be discussed, what can be done, what is done, and what challenges remain in the use of AI especially in the context of media applications and services. The talk is not so much focused on the details and fundamentals of deep learning, but rather on a practical perspective on how recent advances in this field can be utilised in use-cases in the media domain, especially with respect to audio-visual content and in the broadcasting domain.
Rapid prototyping quant research ml models using the qu sandboxQuantUniversity
QU Summer school 2020 speaker Series - Session 7
A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Managing Machine Learning Models in the Financial Industry
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
QU Summer school 2020 speaker Series - Session 8
A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Explainable AI and Bias in Machine Learning: A Financial Industry perspective
In the last year or so, there has been a significant interest in AI explainability, fairness, and bias. Many regulatory efforts are being proposed to reign in the uncontrolled deployment of AI. Companies on the other hand are grappling with complex black boxes and are figuring out how to build models that are explainable, fair, and bias-free. Many startups are working on interesting technologies to address these issues. In this session, we will discuss AI explainability and Bias from an entrepreneur and investor perspective. and have a discussion on what the opportunities and challenges are and what the future looks like for explainable AI
RECENT PHD RESEARCH TOPIC IDEAS FOR COMPUTER SCIENCE ENGINEERING 2020 Exclusi...Tutors India
Artificial intelligence (AI) based data mining and pattern recognition method for knowledge extraction & decision-making process over the cloud environment. Design and implementation of autonomic resource provisioning and a scheduling method to satisfy the user QoS requirement in a cloud platform. The implementation of privacy-aware efficient resource scheduling and load balancing approach for big data storage system. Location-based image retrieval system using deep neural network and image Features Information Fusion technique. To detect network intrusion/attacks over the cloud data using soft computing and optimization technique.
IC-SDV 2019: AI meets IP: There is Nothing Artificial about it - Srinivasan P...Dr. Haxel Consult
Artificial intelligence is a global phenomenon, a technology that has arrived. No industry will be untouched by the changes and disruption these technologies bring. With the rapidly changing innovation landscape, patent offices are discussing the interplay between AI and patents. Corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policy makers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses. Patent analysts will have to respond to this changing environment by being more global in their perspective and will need analytic skills to deal with growing amount of data. The presentation will focus on these aspects and will highlight recent developments in AI methods and the breadth of AI applications that are of importance to patent searchers, analysts, and decision-makers. We will discuss some basics of AI and then zoom in on the neural networks based natural language processing methods and discuss their applications for patent corpus.
Learn how artificial intelligence (AI) and machine learning are revolutionizing industries — this course will introduce key concepts and illustrate the role of machine learning, data science techniques, and AI through examples and case studies from the investment industry. The presentation uses simple mathematics and basic statistics to provide an intuitive understanding of machine learning, as used by firms, to augment traditional decision making.
https://quforindia.splashthat.com/
In 2009 author and motivational speaker Simon Sinek delivered the now-classic TED talk “Start with why”. Viewed by over 28 million people, “Start with Why” is the third most popular TED video of all time and it teaches us that great leaders and companies inspire us to take action by focusing on the WHY over the “what” or the “how”. In this talk we’ll ask how applied data and computational scientists can use the power of WHY to frame problems, inspire others, and give them answers to business questions they might never think of asking.
Bio
Jessica Stauth is a Managing Director in Fidelity Labs, an internal startup incubator with a mission to create new fintech businesses that drive growth for the firm. Dr. Stauth previously held roles as Managing Director of Portfolio Management, Research, and Trading at Quantopian, a crowd-sourced systematic hedge fund based in Boston, Director of Quant Product Strategy for Thomson Reuters (now Refinitiv), and as a Senior Quant Researcher at the StarMine Corporation, where she built global stock selection models including the design and implementation of the StarMine Short Interest model. Dr. Stauth holds a PhD in Biophysics from UC Berkeley, where her research focused on computational neuroscience.
This workshop will look into ways to create synthetic data from lending club loan record datasets alongside comparing characteristics and statistical properties of real and synthetic datasets. There will also be discussions into building machine learning models for predicting interest rates using real and synthetic datasets and evaluating the performance and discuss the advantages and disadvantages of using synthetic datasets as a proxy for real datasets
This workshop will look into ways to create synthetic data from lending club loan record datasets alongside comparing characteristics and statistical properties of real and synthetic datasets. There will also be discussions into building machine learning models for predicting interest rates using real and synthetic datasets and evaluating the performance and discuss the advantages and disadvantages of using synthetic datasets as a proxy for real datasets
Learnbay provides industry accredited data science courses in Bangalore. We understand the conjugation of technology in the field of Data science hence we offer significant courses like Machine learning, Tensor flow, IBM watson, Google Cloud platform, Tableau, Hadoop, time series, R and Python. With authentic real time industry projects. Students will be efficient by being certified by IBM. Around hundreds of students are placed in promising companies for data science role. Choosing Learnbay you will reach the most aspiring job of present and future.
Learnbay data science course covers Data Science with Python,Artificial Intelligence with Python, Deep Learning using Tensor-Flow. These topics are covered and co-developed with IBM.
Dynniq & GoDataDriven - Shaping the future of traffic with IoT and AIBigDataExpo
Dynniq is a high-tech, innovative company offering smart mobility solutions and services internationally. We will present advanced IoT use cases Dynniq is working on, and share how GoDataDriven helps set up an AI capability. We will share our learnings, and show what makes data science in the mobility domain unique.
Big data visualization allotting by r and python with gui toolsSK Ahammad Fahad
A tremendous amount of data comes with a vast amount of knowledge. Decent use of the persistent information can assist to overcome provocations and support to establish further sophisticated judgment. Data visualization techniques are authenticated scientifically as thousand times reliable rather than textual representation. The premature data visualization system met some difficulties and there has some solution to handle this kind of big quantity of data. Data science used two distinct languages Python and R to visualize big data undeviatingly. There also have a lot of tools in operating business. This paper is focused on the visualization technique of Python and R. R appears including the extraordinary visualization library alike ggplot2, leaflet, and lattice to defeat the provocation of the extensive volume. Python has several particular libraries for data visualization. Commonly they are Bokeh, Seaborn, Altair, ggplot and Pygal. Also, with most modern, secure and powerful zero coding GUI's accessories to describe big data visualization for genuine recognition with practical determination. Method and process of visual description of data are significant to recover specific knowledge from the large-scale data.
International Journal of Advances in Artificial Intelligence (IJAAI)ijfcst journal
International Journal of Advances in Artificial Intelligence (IJAAI) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Artificial Intelligence. The journal focuses on all technical and practical aspects of Artificial Intelligence. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Artificial Intelligence and establishing new collaborations in these areas.
Artificial Intelligence (AI) is nowadays used frequently in many application domains. Although sometimes considered only as an afterthought in the public discussion compared to other domains such as health, transportation, and manufacturing, the media domain is also transformed by AI enabling new opportunities, from content creation e.g. “robojournalism” and individualised content to optimisation of the content production and distribution. Underlaying many of these new opportunities is the use of AI in its current reincarnation as deep learning for understanding the audio-visual content by extracting structured information from the unstructured data, the audio-visual content.
In this talk the current understanding and trends of AI will therefore be discussed, what can be done, what is done, and what challenges remain in the use of AI especially in the context of media applications and services. The talk is not so much focused on the details and fundamentals of deep learning, but rather on a practical perspective on how recent advances in this field can be utilised in use-cases in the media domain, especially with respect to audio-visual content and in the broadcasting domain.
Rapid prototyping quant research ml models using the qu sandboxQuantUniversity
QU Summer school 2020 speaker Series - Session 7
A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Managing Machine Learning Models in the Financial Industry
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
QU Summer school 2020 speaker Series - Session 8
A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Explainable AI and Bias in Machine Learning: A Financial Industry perspective
In the last year or so, there has been a significant interest in AI explainability, fairness, and bias. Many regulatory efforts are being proposed to reign in the uncontrolled deployment of AI. Companies on the other hand are grappling with complex black boxes and are figuring out how to build models that are explainable, fair, and bias-free. Many startups are working on interesting technologies to address these issues. In this session, we will discuss AI explainability and Bias from an entrepreneur and investor perspective. and have a discussion on what the opportunities and challenges are and what the future looks like for explainable AI
RECENT PHD RESEARCH TOPIC IDEAS FOR COMPUTER SCIENCE ENGINEERING 2020 Exclusi...Tutors India
Artificial intelligence (AI) based data mining and pattern recognition method for knowledge extraction & decision-making process over the cloud environment. Design and implementation of autonomic resource provisioning and a scheduling method to satisfy the user QoS requirement in a cloud platform. The implementation of privacy-aware efficient resource scheduling and load balancing approach for big data storage system. Location-based image retrieval system using deep neural network and image Features Information Fusion technique. To detect network intrusion/attacks over the cloud data using soft computing and optimization technique.
IC-SDV 2019: AI meets IP: There is Nothing Artificial about it - Srinivasan P...Dr. Haxel Consult
Artificial intelligence is a global phenomenon, a technology that has arrived. No industry will be untouched by the changes and disruption these technologies bring. With the rapidly changing innovation landscape, patent offices are discussing the interplay between AI and patents. Corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policy makers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses. Patent analysts will have to respond to this changing environment by being more global in their perspective and will need analytic skills to deal with growing amount of data. The presentation will focus on these aspects and will highlight recent developments in AI methods and the breadth of AI applications that are of importance to patent searchers, analysts, and decision-makers. We will discuss some basics of AI and then zoom in on the neural networks based natural language processing methods and discuss their applications for patent corpus.
Learn how artificial intelligence (AI) and machine learning are revolutionizing industries — this course will introduce key concepts and illustrate the role of machine learning, data science techniques, and AI through examples and case studies from the investment industry. The presentation uses simple mathematics and basic statistics to provide an intuitive understanding of machine learning, as used by firms, to augment traditional decision making.
https://quforindia.splashthat.com/
In 2009 author and motivational speaker Simon Sinek delivered the now-classic TED talk “Start with why”. Viewed by over 28 million people, “Start with Why” is the third most popular TED video of all time and it teaches us that great leaders and companies inspire us to take action by focusing on the WHY over the “what” or the “how”. In this talk we’ll ask how applied data and computational scientists can use the power of WHY to frame problems, inspire others, and give them answers to business questions they might never think of asking.
Bio
Jessica Stauth is a Managing Director in Fidelity Labs, an internal startup incubator with a mission to create new fintech businesses that drive growth for the firm. Dr. Stauth previously held roles as Managing Director of Portfolio Management, Research, and Trading at Quantopian, a crowd-sourced systematic hedge fund based in Boston, Director of Quant Product Strategy for Thomson Reuters (now Refinitiv), and as a Senior Quant Researcher at the StarMine Corporation, where she built global stock selection models including the design and implementation of the StarMine Short Interest model. Dr. Stauth holds a PhD in Biophysics from UC Berkeley, where her research focused on computational neuroscience.
This workshop will look into ways to create synthetic data from lending club loan record datasets alongside comparing characteristics and statistical properties of real and synthetic datasets. There will also be discussions into building machine learning models for predicting interest rates using real and synthetic datasets and evaluating the performance and discuss the advantages and disadvantages of using synthetic datasets as a proxy for real datasets
This workshop will look into ways to create synthetic data from lending club loan record datasets alongside comparing characteristics and statistical properties of real and synthetic datasets. There will also be discussions into building machine learning models for predicting interest rates using real and synthetic datasets and evaluating the performance and discuss the advantages and disadvantages of using synthetic datasets as a proxy for real datasets
Learnbay provides industry accredited data science courses in Bangalore. We understand the conjugation of technology in the field of Data science hence we offer significant courses like Machine learning, Tensor flow, IBM watson, Google Cloud platform, Tableau, Hadoop, time series, R and Python. With authentic real time industry projects. Students will be efficient by being certified by IBM. Around hundreds of students are placed in promising companies for data science role. Choosing Learnbay you will reach the most aspiring job of present and future.
Learnbay data science course covers Data Science with Python,Artificial Intelligence with Python, Deep Learning using Tensor-Flow. These topics are covered and co-developed with IBM.
Dynniq & GoDataDriven - Shaping the future of traffic with IoT and AIBigDataExpo
Dynniq is a high-tech, innovative company offering smart mobility solutions and services internationally. We will present advanced IoT use cases Dynniq is working on, and share how GoDataDriven helps set up an AI capability. We will share our learnings, and show what makes data science in the mobility domain unique.
Big data visualization allotting by r and python with gui toolsSK Ahammad Fahad
A tremendous amount of data comes with a vast amount of knowledge. Decent use of the persistent information can assist to overcome provocations and support to establish further sophisticated judgment. Data visualization techniques are authenticated scientifically as thousand times reliable rather than textual representation. The premature data visualization system met some difficulties and there has some solution to handle this kind of big quantity of data. Data science used two distinct languages Python and R to visualize big data undeviatingly. There also have a lot of tools in operating business. This paper is focused on the visualization technique of Python and R. R appears including the extraordinary visualization library alike ggplot2, leaflet, and lattice to defeat the provocation of the extensive volume. Python has several particular libraries for data visualization. Commonly they are Bokeh, Seaborn, Altair, ggplot and Pygal. Also, with most modern, secure and powerful zero coding GUI's accessories to describe big data visualization for genuine recognition with practical determination. Method and process of visual description of data are significant to recover specific knowledge from the large-scale data.
International Journal of Advances in Artificial Intelligence (IJAAI)ijfcst journal
International Journal of Advances in Artificial Intelligence (IJAAI) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Artificial Intelligence. The journal focuses on all technical and practical aspects of Artificial Intelligence. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Artificial Intelligence and establishing new collaborations in these areas.
Advanced Software Engineering Program with IIT MadrasMamathaSharma4
Advanced Certification in Software Engineering for
Cloud, Blockchain & IoT-https://www.greatlearning.in/advanced-software-engineering-course-iit-madras
In the bustling city of Chandigarh, where innovation meets tradition, the field of science is witnessing a revolution. As the world advances into the digital age, the demand for skilled professionals in computer science is soaring. With a myriad of opportunities unfolding, science students, particularly those pursuing B.Tech in Computer Science, are poised to embark on exciting career trajectories. We delve into the futuristic career prospects awaiting aspiring technocrats in Chandigarh and explore the top B.Tech college in the vicinity.
NIMT Computer Science and Engineering Department is committed for research at the intersections of knowledge domains within computer science and between computer science and other disciplines, especially where such research can empower the human potential in service to science and society.
SOP or Personal Statement for London South Bank Universityaziznitham
Personal statement or SOP is the statement of own individuals stuff. This is the only for your understanding how to write SOP or personal statement and what should be mentioned in it. On the basis of this general SOP, you can make your own.
One who belongs to "Computer Science and Engineering" or "Software Engineering" background can write similar but with own words.
Smart SE: Recurrent Education Program of IoT and AI for BusinessHironori Washizaki
Hironori Washizaki, "Smart SE: Recurrent Education Program of IoT and AI for Business," 2021 IEEE International Conference on Educational Technology (ICET), Keynote, Online, June 20, 2021.
Finely Chair talk: Every company is an AI company - and why Universities sho...Amit Sheth
Video: https://youtu.be/ZS8rGSzb_9I
The context of this talk is this statement from the host institution's provost: "We are trying to mobilize our campus activities around AI.” I connect academic initiatives in Interdisciplinary AI with industry needs.
--- Original abstract -----
Every company now is an AI company: Now, Near Future, or Distant Future?
Amit Sheth, AI Institute, University of South Carolina
“Every company now is an AI company. The industrial companies are changing, the supply chain…every single sector, it’s not only tech.” said Steven Pagliuca, CEO of Bain Capital at the 2019 World Economic Forum. With this statement as the context, I will provide an overview of AI landscape -- what AI capabilities are for real, what is being oversold, what is nonexistent, what is unlikely in our lifetime. I will also provide an anecdote-supported review through a broad variety of current and eminent applications of AI that rely on some of the well-developed and emerging AI capabilities. The objective is to help those considering AI applications start thinking of new business opportunities, new products and services, and new revenue/business models in the context of rapid penetration of AI technologies everywhere. I will seek to answer: Is AI just hype or something already happening? If it has not happened in your industry, is it impending? Do bad impacts of AI outweigh the good?
There is immense scope of computer engineering in India. That is why a plethora of students aspire to make their career in the field. If you are looking for one of the top engineering colleges in India, then consider Avantika University. It is India's first design-centered university.
To know more details, visit us at : http://avantikauniversity.edu.in/engineering-colleges/scope-of-computer-engineering.php
Pursue M.Tech in Computer Science with specialization in Data Science and Mac...MamathaSharma4
Industry oriented Masters degree program with specialization in data science and machine learning, for working professionals- https://www.greatlearning.in/mtech-computer-science-data-science-srm
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Chetan Khatri
What is Data Science?
What is Machine Learning, Deep Learning, and AI?
Motivation
Philosophy of Artificial Intelligence (AI)
Role of AI in Daily life
Use cases/Applications
Tools & Technologies
Challenges: Bias, Fake Content, Digital Psychography, Security
Detect Fake Content with “AI”
Learning Path
Career Path
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...Chetan Khatri
Pragmatic presentation on Penetration testing for Data-Driven Platforms.
Agenda:
- Motivation
- Information Security - Ethics.
- Encryption
- Authentication
- Information Security & Potential threats with Open Source World.
- Find vulnerabilities.
- Checklist before using any Open Source library.
- Vulnerabilities report.
- Penetration Testing for Data-Driven Developments.
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionChetan Khatri
Scala Toronto July 2019 event at 500px.
Pure Functional API Integration
Apache Spark Internals tuning
Performance tuning
Query execution plan optimisation
Cats Effects for switching execution model runtime.
Discovery / experience with Monix, Scala Future.
No more struggles with Apache Spark workloads in productionChetan Khatri
Paris Scala Group Event May 2019, No more struggles with Apache Spark workloads in production.
Apache Spark
Primary data structures (RDD, DataSet, Dataframe)
Pragmatic explanation - executors, cores, containers, stage, job, a task in Spark.
Parallel read from JDBC: Challenges and best practices.
Bulk Load API vs JDBC write
An optimization strategy for Joins: SortMergeJoin vs BroadcastHashJoin
Avoid unnecessary shuffle
Alternative to spark default sort
Why dropDuplicates() doesn’t result consistency, What is alternative
Optimize Spark stage generation plan
Predicate pushdown with partitioning and bucketing
Why not to use Scala Concurrent ‘Future’ explicitly!
No more struggles with Apache Spark (PySpark) workloads in production, Chetan Khatri, Data Science Practice Leader.
Accionlabs India. PyconLT’19, May 26 - Vilnius Lithuania
Fossasia ai-ml technologies and application for product development-chetan kh...Chetan Khatri
Train at GPU and Inference at Mobile, Artificial Intelligence / Machine learning Technologies and Applications for AI Driven Product Development. Talk at FOSSASIA 2018, Singapore
NIDM (National Institute Of Digital Marketing) Bangalore Is One Of The Leading & best Digital Marketing Institute In Bangalore, India And We Have Brand Value For The Quality Of Education Which We Provide.
www.nidmindia.com
New Explore Careers and College Majors 2024.pdfDr. Mary Askew
Explore Careers and College Majors is a new online, interactive, self-guided career, major and college planning system.
The career system works on all devices!
For more Information, go to https://bit.ly/3SW5w8W
1. Panel Discussion on
Contribution by The Department of CS,
Kachchh University to Industry and Research.
Speaker I : Chetan Khatri, Technical Execution
Manager, Nazara Games.
Speaker II : Prof. Devji Chhanga, Head of the
Dept. of CS, University of Kachchh.
2. What we are ?
l
We are Industrial Best practice oriented +
Research oriented.
l
Our students are working at Multiple domains in
Industries from startup to MNC's, domains are
not limited to Telecom, gaming, Banking,
Insurance, Healthcare etc.
l
Our students are working with leading industries
and leading team members of IITians and
others.
l
Our Master program (Msc. CA & IT) has world
class syllabus , that provides cutting edge & high
pay scale opportunities in market.
3. Where our students are working ?
Employers
Roles
l
Software Developer
l
Senior Developer
l
Principal Engineer
l
Data Scientist
l
Team Lead
l
Technical Execution Manager
4. With whom our students are working
?
Vendors
Roles
l
Chief Architect
l
Stackholder
l
Technical Execution Manager
l
Product owner
5. With whom our students are working
? (Conti...)
Service Partner
6. With whom our students are working
? (Conti...)
Service Partner
Roles
l
Chief Architect
l
Stackholder
l
Technical Execution Manager
l
Product owner
8. Team Members are from different
sources & Industries (conti...)
Industries
9. l
Big tickets in Placement Year 2015
(Value of Time)
Kachchh Uni LDRP Atmiya SVNIT IIT-G
0
2
4
6
8
10
12
Kachchh Uni
LDRP
Atmiya
SVNIT
IIT-G
10. Value of Cost
Kachchh Uni LDRP Atmiya SVNIT DAIICT
0
50000
100000
150000
200000
250000
300000
Kachchh Uni
LDRP
Atmiya
SVNIT
DAIICT
11. Return on Investment (ROI)
l
If we take 60,000 as fee cost and earned
package is 9 LPA then it would be 1500 %
Return on Investment (ROI).
l
The Department of Computer Science has
earned Big Ticket by grabing Highest Package
from Government Universities in Gujarat.
12. Return on Investment (ROI) (conti...)
Kachchh Uni LDRP Atmiya SVNIT
0
200
400
600
800
1000
1200
1400
1600
1800
Kachchh Uni
LDRP
Atmiya
SVNIT
13. Exclusive Big Ticket Annoucement
l
Big Data, Data Science, Machine Learning
Specialization courses in Msc (CA & IT) program
from starting July 2016.
l
We are the first Governement University who
has Big Data Science and ML specialization
courses in Master's in INDIA.
l
Amazing exprience with Data Science + ML +
Internet of Things (IoT).
14. Data Science Specialization Program | Value
of cost
Kachchh University Berkeley Newyork University USC
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
Kachchh University
Berkeley
Newyork University
USC
16. Data Science
Collect Store Analyze Consume
A
iOS Android
Web Apps
Logstash
Amazon
RDS
Amazon
DynamoDB
Amazon
ES
Amazon
S3
Apache
Kafka
Amazon
Glacier
Amazon
Kinesis
Amazon
DynamoD
B
Amazon
Redshift
Impal
a
Pig
Amazon ML
Streami
ng
Amazon
Kinesis
AWS
Lambda
A
m
a
z
o
n
El
a
st
ic
M
a
p
R
e
d
u
c
e
Amazon
ElastiCach
e
SearchSQLNoSQL
Cache
StreamProcessingBatchInteractive
Logging
Stream
Storage
IoTApplications
FileStorage
Analysis&Visualization
Hot
Col
d
Warm
Ho
t
Slo
w
Hot
ML
Fas
t
Fas
t
Amazon
QuickSight
Transactional
Data
File Data
Stream Data
Notebook
s
Predictions
Apps & APIs
Mobile
Apps
IDE
Search Data
ETL
Reference Architecture