How does the neural network work, types of neural networks, advantages and applications of neural networks, a use case of neural network, backpropagation and gradient descent, convolutional neural networks, recurrent neural network, vanishing and exploding gradient problem, long short term memory
Deep learning and its applications, Neural Network, Training Neural Networks, Deep Learning Libraries, TensorFlow, Data Flow Graph, Use Case Implementation using TensorFlow, TensorFlow Object Detection, Deep Learning Frameworks, Image Recognition, Types of Recurrent Neural Network, Working of LSTMs, Deep Learning Applications
Image recognition is a field of artificial intelligence that teaches computers to identify and understand the contents of digital images. It has many applications including face recognition, medical imaging, autonomous vehicles, photo organization and more. The goal of this document is to provide a basic introduction and overview of image recognition concepts and techniques for those new to the topic.
This document is a certificate for Sayma Chowdhury for completing an Introduction to Artificial Intelligence course on February 14th, 2022. The certificate code listed is 3253209.
This document is a certificate for Sayma Chowdhury for completing the course "Introduction to Deep Learning with Keras" on February 13th, 2022. The certificate code for this course completion is 3251714.
TensorFlow is an open-source machine learning framework. Sayma Chowdhury completed a course on TensorFlow for Beginners on February 12th, 2022 and received a certificate with code 3249942. The document provides information about a TensorFlow course certificate for Sayma Chowdhury.
This certificate recognizes Vijayananda Mohire as a Member in good standing through December 2021, denoting a personal and professional commitment to the advancement of technology.
This certificate recognizes Manu Mitra as a Member in good standing through December 2022, denoting a personal and professional commitment to the advancement of technology.
How does the neural network work, types of neural networks, advantages and applications of neural networks, a use case of neural network, backpropagation and gradient descent, convolutional neural networks, recurrent neural network, vanishing and exploding gradient problem, long short term memory
Deep learning and its applications, Neural Network, Training Neural Networks, Deep Learning Libraries, TensorFlow, Data Flow Graph, Use Case Implementation using TensorFlow, TensorFlow Object Detection, Deep Learning Frameworks, Image Recognition, Types of Recurrent Neural Network, Working of LSTMs, Deep Learning Applications
Image recognition is a field of artificial intelligence that teaches computers to identify and understand the contents of digital images. It has many applications including face recognition, medical imaging, autonomous vehicles, photo organization and more. The goal of this document is to provide a basic introduction and overview of image recognition concepts and techniques for those new to the topic.
This document is a certificate for Sayma Chowdhury for completing an Introduction to Artificial Intelligence course on February 14th, 2022. The certificate code listed is 3253209.
This document is a certificate for Sayma Chowdhury for completing the course "Introduction to Deep Learning with Keras" on February 13th, 2022. The certificate code for this course completion is 3251714.
TensorFlow is an open-source machine learning framework. Sayma Chowdhury completed a course on TensorFlow for Beginners on February 12th, 2022 and received a certificate with code 3249942. The document provides information about a TensorFlow course certificate for Sayma Chowdhury.
This certificate recognizes Vijayananda Mohire as a Member in good standing through December 2021, denoting a personal and professional commitment to the advancement of technology.
This certificate recognizes Manu Mitra as a Member in good standing through December 2022, denoting a personal and professional commitment to the advancement of technology.
Foundations of Data Science K-Means Clustering in Python - Sayma Chowdhury.pdfSaymaChowdhury1
This document is a certificate confirming that Sayma Chowdhury successfully completed the online course "Foundations of Data Science: K-Means Clustering in Python" offered through Coursera and authorized by University of London, Goldsmiths. The certificate provides Sayma Chowdhury's name, the course name and dates, and a link to verify the authenticity of the certificate which is signed by the instructors of the course.
HarvardX - Digital Humanities Certificate.pdfSaymaChowdhury1
This certificate from edX confirms completion of the HarvardX DH101x course "Introduction to Digital History" by Jane Doe. The course provided an overview of how digital tools and online platforms are transforming the study and communication of history, and explored new approaches to analyzing historical materials and presenting historical narratives using digital media. Jane Doe successfully completed all course requirements to earn this certificate in digital history.
Who needs to be in the team. How to set up your Board. How to select your advisors and mentors. How to create a company culture. How to use company culture to retain talent.
How to prepare for your first investment. Do you need investment. What to include in your pitch deck. How to manage relationships with investors. How to prepare for Series A.
The document certifies Sayma Chowdhury on June 17th, 2022 for understanding startup finance. It provides certification but no details on the specific topics, skills, or level of understanding related to startup finance. The summary is in 3 sentences as requested.
Avoiding common mistakes in building your team. Developing a compelling story about your idea. Avoiding running out of cash. Finding your early customers. Choosing the right legal structure for your business.
How to select your route to market. How to get your first 100 users. How to land your first client. How to do marketing on a budget. How to use analytics for growth. How to grow your sales. How to know everything about your customer.
Do you have the right stuff to be an entrepreneur. How entrepreneurs think up ideas. How entrepreneurs test and refine their ideas. How entrepreneurs talk to their customers. How entrepreneurs move from ideas to action. How entrepreneurs assess competition.
Marketing your business with social media. Building your communities. Sharing your content. Choosing a social media platform. Making social media work for you. Knowing when you're getting social media right.
Psychology of Search, Buying Funnel, Understanding Keyword Organisation, Keyword Match Types, Negative Keywords and Managing Search Terms, Keyword Research, Creating Compelling Ads, Advanced Ad Features, Ad Testing, Ad Extensions, Campaign Types Budget and Reach, Location and Language Targeting, Introduction to Audience Types, how to segment data and create lists
Developing a vision for content marketing success, developing business case for content marketing, creating a successful content marketing strategy, targeting customer intent instead of demographics, targeting key influencers, producing help hub and hero content consistently, producing engaging content more frequently, using effective B2C and B2B content marketing tactics, building successful B2C and B2B social media platforms, helping customers find the information they seek, helping key influences effect the buyers decision making process, measuring content effectiveness, measuring return on marketing investment, improving by experimenting with new initiatives, improving effectiveness by becoming more sophisticated and mature, content marketing in the foreseeable futur B2C evision
Introduction to the Components of Hadoop for BeginnersSaymaChowdhury1
Hadoop is an open-source software framework used for distributed storage and processing of large datasets across clusters of computers. It uses MapReduce as a programming model and HDFS for storage. This document provides an introduction to the key components of Hadoop including HDFS, MapReduce, YARN, and Hive which are used together to process and analyze large datasets in parallel across clusters of computers.
Big data tools allow organizations to collect and analyze large amounts of unstructured data to gain valuable insights. This document provides an introduction to common big data tools for beginners, including Hadoop, Spark, Hive and more. The reader will learn the basics of these tools and how they can be used to extract meaningful information from vast datasets.
Introduction to Apache Spark Data Analytics for BeginnersSaymaChowdhury1
Apache Spark is a popular framework for large-scale data processing. This document provides an introduction to Apache Spark data analytics for beginners, covering the basics of working with Spark. The certificate code for the course is 3263024.
NoSQL Databases, CRUD Operations, Indexing and Aggregation, Replication and Sharding, Developing Java and NodeJS Application with MongoDB, MongoDB Cluster Operations
Foundations of Data Science K-Means Clustering in Python - Sayma Chowdhury.pdfSaymaChowdhury1
This document is a certificate confirming that Sayma Chowdhury successfully completed the online course "Foundations of Data Science: K-Means Clustering in Python" offered through Coursera and authorized by University of London, Goldsmiths. The certificate provides Sayma Chowdhury's name, the course name and dates, and a link to verify the authenticity of the certificate which is signed by the instructors of the course.
HarvardX - Digital Humanities Certificate.pdfSaymaChowdhury1
This certificate from edX confirms completion of the HarvardX DH101x course "Introduction to Digital History" by Jane Doe. The course provided an overview of how digital tools and online platforms are transforming the study and communication of history, and explored new approaches to analyzing historical materials and presenting historical narratives using digital media. Jane Doe successfully completed all course requirements to earn this certificate in digital history.
Who needs to be in the team. How to set up your Board. How to select your advisors and mentors. How to create a company culture. How to use company culture to retain talent.
How to prepare for your first investment. Do you need investment. What to include in your pitch deck. How to manage relationships with investors. How to prepare for Series A.
The document certifies Sayma Chowdhury on June 17th, 2022 for understanding startup finance. It provides certification but no details on the specific topics, skills, or level of understanding related to startup finance. The summary is in 3 sentences as requested.
Avoiding common mistakes in building your team. Developing a compelling story about your idea. Avoiding running out of cash. Finding your early customers. Choosing the right legal structure for your business.
How to select your route to market. How to get your first 100 users. How to land your first client. How to do marketing on a budget. How to use analytics for growth. How to grow your sales. How to know everything about your customer.
Do you have the right stuff to be an entrepreneur. How entrepreneurs think up ideas. How entrepreneurs test and refine their ideas. How entrepreneurs talk to their customers. How entrepreneurs move from ideas to action. How entrepreneurs assess competition.
Marketing your business with social media. Building your communities. Sharing your content. Choosing a social media platform. Making social media work for you. Knowing when you're getting social media right.
Psychology of Search, Buying Funnel, Understanding Keyword Organisation, Keyword Match Types, Negative Keywords and Managing Search Terms, Keyword Research, Creating Compelling Ads, Advanced Ad Features, Ad Testing, Ad Extensions, Campaign Types Budget and Reach, Location and Language Targeting, Introduction to Audience Types, how to segment data and create lists
Developing a vision for content marketing success, developing business case for content marketing, creating a successful content marketing strategy, targeting customer intent instead of demographics, targeting key influencers, producing help hub and hero content consistently, producing engaging content more frequently, using effective B2C and B2B content marketing tactics, building successful B2C and B2B social media platforms, helping customers find the information they seek, helping key influences effect the buyers decision making process, measuring content effectiveness, measuring return on marketing investment, improving by experimenting with new initiatives, improving effectiveness by becoming more sophisticated and mature, content marketing in the foreseeable futur B2C evision
Introduction to the Components of Hadoop for BeginnersSaymaChowdhury1
Hadoop is an open-source software framework used for distributed storage and processing of large datasets across clusters of computers. It uses MapReduce as a programming model and HDFS for storage. This document provides an introduction to the key components of Hadoop including HDFS, MapReduce, YARN, and Hive which are used together to process and analyze large datasets in parallel across clusters of computers.
Big data tools allow organizations to collect and analyze large amounts of unstructured data to gain valuable insights. This document provides an introduction to common big data tools for beginners, including Hadoop, Spark, Hive and more. The reader will learn the basics of these tools and how they can be used to extract meaningful information from vast datasets.
Introduction to Apache Spark Data Analytics for BeginnersSaymaChowdhury1
Apache Spark is a popular framework for large-scale data processing. This document provides an introduction to Apache Spark data analytics for beginners, covering the basics of working with Spark. The certificate code for the course is 3263024.
NoSQL Databases, CRUD Operations, Indexing and Aggregation, Replication and Sharding, Developing Java and NodeJS Application with MongoDB, MongoDB Cluster Operations
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"sameer shah
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.