Some examples and motivation for creating data structures from nothing but functions - Church Encoding! There's particular detail on how it can make free monads more efficient.
Airbnb aims to democratize data within the company by building a graph database of all internal data resources connected by relationships. This graph is queried through a search interface to help employees explore, discover, and build trust in company data. Challenges include modeling complex data dependencies and proxy nodes, merging graph updates from different sources, and designing a data-dense interface simply. Future goals are to gamify content production, deliver recommendations, certify trusted content, and analyze the information network.
Booz Allen Hamilton created the Field Guide to Data Science to help organizations and missions understand how to make use of data as a resource. The Second Edition of the Field Guide, updated with new features and content, delivers our latest insights in a fast-changing field. http://bit.ly/1O78U42
Power BI is a self-service business intelligence tool that allows users to analyze and visualize data. It consists of Power BI Desktop, the Power BI web service, and the Power BI mobile app. Power BI Desktop is used to build reports and dashboards locally, while the web service allows users to publish, share, and collaborate on reports and dashboards online. To create a dashboard in Power BI, a user would connect to a data source, build visualizations with the data, publish the report to the web, combine reports into a dashboard, and then share the dashboard.
The growth hacking roadmap that summarizes how startups can maximize the growth of their most valuable customers. It also summarizes the actionable analytics growth hackers should be using including cohort analysis, user testing and key performance indicators.
Clickbait: A Guide To Writing Un-Ignorable HeadlinesVenngage
We looked at some of the top performing content on social media, from some of the top publications on the web. From this, we were able to figure out the recipe for crafting a click-worthy title. Here is what we learned...
This document discusses Apache Ranger and Apache Atlas for security and governance in Hadoop. It provides an overview of Ranger's centralized authorization and auditing capabilities for Hadoop components using policies. It also describes Atlas' capabilities for metadata management, data lineage, classification using tags, and integrations with Ranger for classification-based security. The document concludes with a demo and Q&A section.
Muga Nishizawa discusses Embulk, an open-source bulk data loader. Embulk loads records from various sources to various targets in parallel using plugins. Treasure Data customers use Embulk to upload different file formats and data sources to their TD database. While Embulk is focused on bulk loading, TD also develops additional tools to generate Embulk configurations, manage loads over time, and scale Embulk using a MapReduce executor on Hadoop clusters for very large data loads.
This document contains the agenda for a Power Query event. It includes sections on the sponsor, organizers, presenter Marco Pozzan, and an agenda with topics like Power Query basics, functions, error handling, privacy settings, and demos. The event aims to teach participants about Power Query's capabilities for data transformation, integration, and analysis.
Data Discovery at Databricks with AmundsenDatabricks
Databricks used to use a static manually maintained wiki page for internal data exploration. We will discuss how we leverage Amundsen, an open source data discovery tool from Linux Foundation AI & Data, to improve productivity with trust by surfacing the most relevant dataset and SQL analytics dashboard with its important information programmatically at Databricks internally.
We will also talk about how we integrate Amundsen with Databricks world class infrastructure to surface metadata including:
Surface the most popular tables used within Databricks
Support fuzzy search and facet search for dataset- Surface rich metadata on datasets:
Lineage information (downstream table, upstream table, downstream jobs, downstream users)
Dataset owner
Dataset frequent users
Delta extend metadata (e.g change history)
ETL job that generates the dataset
Column stats on numeric type columns
Dashboards that use the given dataset
Use Databricks data tab to show the sample data
Surface metadata on dashboards including: create time, last update time, tables used, etc
Last but not least, we will discuss how we incorporate internal user feedback and provide the same discovery productivity improvements for Databricks customers in the future.
Power BI has become a product with a ton of exciting features. This presentation will give an overview of some of them, including Power BI Desktop, Power BI service, what’s new, integration with other services, Power BI premium, and administration.
Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction Mark Ginnebaugh
Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.
You will learn:
* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!
Tableau is a data visualization software company founded in 2003 that was acquired by Salesforce in 2019. It offers a suite of products for data preparation, visualization, sharing, and analytics. The Tableau platform is powered by its VizQL technology and allows users to connect to various data sources, prepare data, create interactive visualizations, dashboards, and stories, and share workbooks on Tableau Server or Tableau Online. Key products include Tableau Desktop, Tableau Server, Tableau Online, Tableau Reader and Tableau Mobile.
This document discusses better collaboration between agencies and clients. It notes that historically, agencies did not provide clients with a full understanding of the creative process or ideas, and clients did not know how to properly evaluate work. It advocates that agencies start presentations with the agreed upon creative brief to provide necessary context before presenting ideas. Agencies should tell a story that bridges the brief to the final idea, giving clients a complete understanding. The document also provides models for properly evaluating ideas and ensuring collaborative discussions between agencies and clients.
David Macleod presented on his use of IDEA software to analyze Falkirk Council's payment data to detect duplicate invoice payments. Over the past 4 years, IDEA analysis identified 283 duplicate payments totaling £211,057. In the current fiscal year through October, 50 duplicates totaling £51,017 were found. IDEA allowed comprehensive matching of payment records to detect non-exact duplicates that may have otherwise gone unnoticed.
Power BI Training | Getting Started with Power BI | Power BI Tutorial | Power...Edureka!
This Edureka tutorial on "Getting started with Power BI" will provide you the fundamental knowledge of Power BI. Below are the topics covered in this tutorial:
1. What is Self Service Business Intelligence?
2. Why Power BI?
3. What is Power BI?
4. Demo on Power BI
All about Zookeeper and ClickHouse Keeper.pdfAltinity Ltd
ClickHouse clusters depend on ZooKeeper to handle replication and distributed DDL commands. In this Altinity webinar, we’ll explain why ZooKeeper is necessary, how it works, and introduce the new built-in replacement named ClickHouse Keeper. You’ll learn practical tips to care for ZooKeeper in sickness and health. You’ll also learn how/when to use ClickHouse Keeper. We will share our recommendations for keeping that happy as well.
Enterprise search promises to make all organizational content findable through a single search interface. However, simply implementing search technology is not enough - content must be well-organized and metadata-rich. Effective enterprise search requires strategies to classify content, extract metadata, govern information, and ensure search interfaces meet user needs across multiple devices. The enterprise search market offers specialized and integrated solutions from various vendors, with trends including social, mobile, and semantic search capabilities.
This presentation explains what data engineering is and describes the data lifecycles phases briefly. I used this presentation during my work as an on-demand instructor at Nooreed.com
Databricks + Snowflake: Catalyzing Data and AI InitiativesDatabricks
"Combining Databricks, the unified analytics platform with Snowflake, the data warehouse built for the cloud is a powerful combo.
Databricks offers the ability to process large amounts of data reliably, including developing scalable AI projects. Snowflake offers the elasticity of a cloud-based data warehouse that centralizes the access to data. Databricks brings the unparalleled utility of being based on a mature distributed big data processing and AI-enabled tool to the table, capable of integrating with nearly every technology, from message queues (e.g. Kafka) to databases (e.g. Snowflake) to object stores (e.g. S3) and AI tools (e.g. Tensorflow).
Key Takeaways:
How Databricks & Snowflake work;
Why they're so powerful;
How Databricks + Snowflake symbiotically catalyze analytics and AI initiatives"
Medicated chewing gum (MCG) is a novel drug delivery system that contains pharmacologically active ingredients in a masticatory gum base. MCG provides advantages over other delivery systems such as fast onset of action, higher bioavailability, and improved patient compliance. The manufacturing process involves softening or melting gum base ingredients and mixing in sweeteners, flavors, and active pharmaceutical ingredients. Release of the API from MCG can be affected by factors like contact time, physicochemical properties of the API, and formulation components. MCG has applications for local oral treatments and systemic drug delivery via absorption in the oral mucosa.
It is impossible to measure or put estimates onto the size of the deep web because the majority of the information is hidden or locked inside databases. Early estimates suggested that the deep web is 4,000 to 5,000 times larger than the surface web.
This document provides an overview of the Inayawan Rubbish Dump Site community in Cebu City, Philippines and the efforts to help improve living conditions there. It discusses the impoverished living situations of families in the community who scavenge the dump site daily. It then describes the establishment of the Inayawan Rubbish Dump Community Center, which started as two shipping containers converted to a classroom and has expanded over years with help from volunteers and donors to now include classrooms, a kitchen, clinic, playground, and other facilities providing hope to the community.
This document provides a list of 10 photographers credited for their photos used in a Haiku Deck presentation on SlideShare. It concludes by encouraging the reader to get started creating their own Haiku Deck presentation.
This document summarizes the emergence of civilization in Japan during the Asuka period from 538 to 710 CE. It describes how Buddhism and Chinese influence grew during this time, including the establishment of Shotoku's 17-article constitution. The Taika reforms later introduced taxation, land distribution, and a provincial system. In 710 CE, Nara was built as the new capital city and became an important religious and cultural center marked by many temples, shrines, and gardens, representing Japan's development as a major Asian civilization.
Bubble gum was first invented in 1906 by Frank Fleer, though it was never sold. Walter Diemer invented the first pink bubble gum called Dubble Bubble in 1928. Most bubble gum is pink today because Diemer only had pink food coloring available when he made his gum. The largest bubble ever blown was 23 inches by Susan Montgomery. North American children spend about half a billion dollars on bubble gum each year. Peanut butter can remove gum from hair. There are 187 flavors of bubble gum.
This document discusses believing in the impossible through hope, faith, challenge, and dreams. It advocates believing in the impossible and provides web addresses for further information on the topic from Richard Dedor's website, blog, and Twitter account. The overall message is that nothing is impossible with hope, faith, and a willingness to take on challenges to achieve one's dreams.
This document provides 10 facts about Japan. It states that Japan consists of over 6,800 islands and has a population of around 127 million people, making it the 10th most populated country. It notes that Tokyo is the capital and largest city, and that Japanese is the official language. The document also mentions that Japan is a world leader in robotics and is home to major companies like Toyota, Sony, and Nintendo.
Nobel Peace Prize 2014: Malala Yousafzai and Kailash Satyarthimaditabalnco
The 2014 Nobel Peace Prize was jointly awarded to Kailash Satyarthi and Malala Yousafzai for their efforts advocating for children's education and fighting against suppression of children. Malala Yousafzai is a teenage education activist from Pakistan who survived an assassination attempt by the Taliban. Kailash Satyarthi is an Indian human rights activist who has worked since 1980 to end child slavery and exploitative child labor through grassroots rescue and rehabilitation efforts.
The Nobel Prize is an annual international award bestowed in several categories by the Nobel Foundation for achievements in physics, chemistry, physiology or medicine, literature, and peace. The prizes are presented in Stockholm, except for the Peace Prize, which is presented in Oslo. Alfred Nobel established the prizes through his will to recognize individuals "who, during the preceding year, shall have conferred the greatest benefit on mankind."
The future can be great for our community, for our province, for the energy industry, for you and me and our children. However, it will require us to embrace positive change and to start the transition now. We can create an Alberta that is a renewable energy powerhouse by energy companies utilizing land and infrastructure they already use to generate renewable energy as well as using fuel cell technology to produce much cleaner energy from hydrocarbons during the transition period. And we can become the supplier of choice for clean and green hydrocarbon products, with extraction, processing and use of final products without emissions, pollution, fresh water and use of harmful chemicals. Why won't we start now? We can do it together!
10 Practical Ways to Be More Efficient at WorkWeekdone.com
Efficiency has always been an ongoing process that you will keep fine tuning for the rest of your life. However, when it comes down to being efficient at work, there are whole industries coming up with solutions. We at Weekdone gathered the 10 best ways to be more efficient at work that we believe to be simple, practical and proven to make you more efficient at work.
This presentation by Kyle Sherman, LinkedIn iOS Developer for the SlideShare iOS app, goes over fixing issues with jittery scroll performance in iOS applications. The presentation goes over the basics of using Instruments to measure and fix problems, tips for using Instruments, and a concrete example from the new LinkedIn iOS flagship application.
Quality is everyone's responsibility at Spotify and testing should be automated for routine tasks to improve efficiency. While testing is important, the overall goal is for it to be a fun process that goes beyond just finding bugs.
The document discusses representing data as functions using Church encoding. It provides examples of representing booleans, natural numbers, and lists as recursive functions. Church encoding allows defining types and operations on those types using lambda calculus alone without needing to declare data types or constructors. This allows implementing any data structure using only functions.
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
The document presents two new algorithms for deciding the siphon/trap property in Petri nets:
1. A reduction to SAT that encodes the problem as a boolean formula that can be solved using existing SAT solvers.
2. A divide-and-conquer approach that decomposes the net into smaller components, computes siphons and traps locally, and combines interface information to evaluate the property in the full net.
Experimental results show the algorithms perform better than brute force approaches and scale efficiently to large nets as long as the nets can be decomposed into components with small interfaces.
Growth of Functions
CMSC 56 | Discrete Mathematical Structure for Computer Science
October 6, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
The binomial theorem provides a formula for expanding binomial expressions of the form (a + b)^n. It states that the terms of the expansion are determined by binomial coefficients. Pascal's triangle is a mathematical arrangement that shows the binomial coefficients and can be used to determine the coefficients in a binomial expansion. The proof of the binomial theorem uses mathematical induction to show that the formula holds true for any positive integer value of n.
The document discusses life without bottom values (⊥) in programming languages. It explains how removing bottom values simplifies language design by avoiding issues like non-termination and making pattern matching and operators like & behave more intuitively. It also discusses how removing bottom values means the language is no longer Turing complete, and explores alternatives like codata to allow modeling infinite computations.
Reactive Programming with RxJava has widely been adopted by both backend services and Android applications alike. Yet, the steep learning curve leaves many developers hesitant about adding it to their own Software tool belt. I was one such developer. Over the past two years, I’ve watched countless videos, read numerous blog posts and attended several conference talks on the subject. Yet, I often left each experience feeling only slightly more knowledgeable, but not quite empowered to start using RxJava in my apps. That’s not going to happen today!
In this talk, we’re going to cover the bare minimum concepts you need to grok, in order to start using RxJava today. In particular, we’re going to focus on:
The 3 O’s: Observable, Observer and Operator
The most common Operators: map(), flatMap(), and filter()
Understanding those Marble Diagrams
Reactive Programming is not going away any time soon. It’s a powerful way to create asynchronous, event-based applications. It allows developers the ability to craft applications that can easily combine multiple network calls, gracefully handle failures, all while providing a snappy user experience. I want everyone to feel comfortable with the basic concepts of RxJava. Today can be your first step...
The document discusses the binomial theorem, which provides a formula for expanding binomial expressions of the form (a + b)^n. It explains that the theorem allows calculating terms of the expansion without using repeated FOIL multiplication. Pascal's triangle is introduced as a way to determine the coefficients of each term. The key points of the binomial theorem are defined, including that the sum of the exponents in each term equals n. An example expansion is shown. Proofs of properties like the coefficients when r=0, 1, n-1, n are provided.
Strassen's algorithm improves on the basic matrix multiplication algorithm which runs in O(N3) time. It achieves this by dividing the matrices into sub-matrices and performing 7 multiplications and 18 additions on the sub-matrices, rather than the 8 multiplications of the basic algorithm. This results in a runtime of O(N2.81) using divide and conquer, providing an asymptotic improvement over the basic O(N3) algorithm.
This document provides formulas and definitions for trigonometric functions including:
- Definitions of trig functions using right triangles and the unit circle
- Domains and ranges of the trig functions
- Periods of trig functions
- Trigonometric identities and formulas
- Inverse trig functions and their properties
- Formulas for conic sections including circles, ellipses, parabolas, and hyperbolas.
The document describes the kinematics of a 6 degree of freedom robotic arm. It presents the Denavit-Hartenberg parameters for defining each link of the robot. It then performs forward kinematics calculations to determine the transformation matrix relating the end effector to the base. It also performs inverse kinematics calculations to solve for the joint angles given a desired end effector pose. The forward and inverse kinematics solutions involve trigonometric functions of the joint angles and geometric parameters of the robot links.
This document provides formulas and definitions for trigonometric functions including the definitions of sine, cosine, and tangent using right triangles and the unit circle. It also includes information on domains, ranges, periods, identities, inverse trig functions, complex numbers, conic sections, and formulas for working with angles in degrees and radians. Key aspects covered are the definitions of trig functions, trig identities, inverse trig functions, and formulas for circles, ellipses, hyperbolas, and parabolas.
Math resources trigonometric_formulas class 11th and 12thDeepak Kumar
This document provides formulas and definitions for trigonometric functions including the definitions of sine, cosine, and tangent using right triangles and the unit circle. It also includes formulas for trigonometric identities, inverse trig functions, complex numbers including DeMoivre's theorem, and conic sections including circles, ellipses, hyperbolas, and parabolas.
The document discusses various sorting algorithms and their time complexities, including counting sort, radix sort, bucket sort, and lower bounds for comparison-based sorting. Counting sort counts the number of occurrences of each key and uses the counts to place the elements in output array in correct positions. Radix sort performs counting sort repeatedly based on each digit of keys written in a given base. Bucket sort distributes elements into buckets based on their hashed values and sorts individual buckets. The time complexity of bucket sort is linear on average if elements are randomly distributed.
Hidden Markov models can be used to model sequential data and detect patterns. The document describes an HMM to detect CpG islands in DNA sequences. It has two states, "CpG island" and "not CpG island". Transition and emission probabilities are estimated from training data. The Viterbi, forward-backward, and Baum-Welch algorithms are used to find the most likely state sequence and re-estimate parameters when the true state sequence is unknown. The model can be extended to higher-order HMMs and different state duration distributions.
Joel Spencer – Finding Needles in Exponential Haystacks Yandex
We discuss two recent methods in which an object with a certain property is sought. In both, using of a straightforward random object would succeed with only exponentially small probability. The new randomized algorithms run efficiently and also give new proofs of the existence of the desired object. In both cases there is a potentially broad use of the methodology.
(i) Consider an instance of k-SAT in which each clause overlaps (has a variable in common, regardless of the negation symbol) with at most d others. Lovasz showed that when ed < 2k (regardless of the number of variables) the conjunction of the clauses was satisfiable. The new approach due to Moser is to start with a random true-false assignment. In a WHILE loop, if any clause is not satisfied we ”fix it” by a random reassignment. The analysis of the algorithm is unusual, connecting the running of the algorithm with certain Tetris patterns, and leading to some algebraic combinatorics. [These results apply in a quite general setting with underlying independent ”coin flips” and bad events (the clause not being satisfied) that depend on only a few of the coin flips.]
(ii) No Outliers. Given n vectors rj in n-space with all coefficients in [−1,+1] one wants a vector x = (x1, ..., xn) with all xi = +1 or −1 so that all dot products x · rj are at most K √ n in absolute value, K an absolute constant. A random x would make x · rj Gaussian but there would be outliers. The existence of such an x was first shown by the speaker. The first algorithm was found by Nikhil Bansal. The approach here, due to Lovett and Meka, is to begin with x = (0, ..., 0) and let it float in a kind of restricted Brownian Motion until all the coordinates hit the boundary.
The document discusses Karnaugh maps (K-maps), which are a tool for representing and simplifying Boolean functions with up to six variables. K-maps arrange the variables in a grid with cells representing minterms or maxterms. Adjacent cells that are both 1s can be combined to eliminate variables. The document provides examples of constructing K-maps from Boolean expressions and using them to find minimum sum of products (SOP) and product of sums (POS) expressions.
This document provides an overview of the topics covered in an introductory mathematics analysis course for business, economics, and social sciences. It includes:
1) A review of key concepts like algebra, subsets of real numbers, properties of operations, and graphing numbers on a number line.
2) An outline of course structure with sections on algebra, algebraic expressions, fractions, and mathematical systems.
3) Examples of problems and their step-by-step solutions covering topics like simplifying expressions, factoring, addition/subtraction of fractions, and properties of real numbers.
The document discusses the merge sort algorithm. It works by recursively dividing an array into two halves, sorting each half, and then merging the sorted halves back together. The key steps are:
1) Divide the array into equal halves recursively until arrays contain a single element.
2) Sort the halves by recursively applying the merge sort algorithm.
3) Merge the sorted halves back into a single sorted array by comparing elements and copying the smaller value into the output array.
How can senior developers bridge the gap to becoming tech leads? How can mentors help them? We'll shine a light from above, a light from below, and we'll see if we can uncover some insights.
Applied category theory: the emerging science of compositionalitykenbot
What do programming, quantum physics, chemistry, neuroscience, systems biology, natural language parsing, causality, network theory, game theory, dynamical systems and database theory have in common?
As functional programmers, we know how useful category theory can be for our work - or perhaps how abstruse and distant it can seem. What is less well known is that applying category theory to the real world is an exciting field of study that has really taken off in just the last few years. It turns out that we share something big with other fields and industries - we want to make big things out of little things without everything going to hell! The key is compositionality, the central idea of category theory.
This talk will introduce the emerging field of applied category theory, with the aims of:
- Giving attendees a broad overview of cutting-edge applications of category theory
- Building an understanding of a small number of the most important core concepts
- Getting attendees excited, inspired to learn more, and equipped to apply some basic concepts to their work
Framework-driven dependency injection, as practiced by many OO programmers, tends to have considerable and underappreciated drawbacks. This talk goes into detail about why.
Functional programming has made great strides in the popular imagination, yet adoption of FP languages has often been challenging for companies, sputtering in fits and starts. Ken has been at the forefront of REA's successful adoption of FP over four years, and will share lessons learnt and traps avoided: how a human-first approach can succeed and scale.
Lenses, or more generally “optics”, are a technique that is indispensable to modern functional programming. However, implementations have veered between two extremes: incredible abstractive power with a steep learning curve; and limited domain-specific uses that can be picked up in minutes. Why can’t we have our cake and eat it too?
Goggles is a new Scala macro built over the powerful & popular Monocle optics library. It uses Scala’s macros and scandalously flexible syntax to create a compiler-checked mini-language to concisely construct, compose and apply optics, with a gentle, familiar interface, and informative compiler errors.
In this talk, I introduce the motivation for lenses, why lens usability is a problem that badly needs solving, and how the Goggles library, with Monocle, addresses this in an important way.
This document summarizes a presentation about the benefits of functional programming. It discusses:
1. The speaker's experience over 2 years using FP at their job, including working on multiple teams and codebases.
2. The key benefits of FP like modularity, abstraction, and composability, which allow programs to remain simple as they grow. Modular code allows local reasoning, abstract code hides unnecessary details, and composable code scales without increasing complexity.
3. Examples of FP concepts used in their code like pure functions, option types, and monoid algebra, and how these improved testability and reduced errors.
4. How the speaker's team adopted FP gradually over time through experimenting with different
Discusses the algebraic properties of types, different kinds of functions and the information that is preserved or lost, and Category Theory concepts that underpin and unify them.
Explains the basic concepts of Category Theory, useful terminology to help understand the literature, and why it's so relevant to software engineering.
Free Monads are a powerful technique that can separate the representation of programs from the messy details of how they get run.
I'll go into the details of how they work, how to use them for fun and profit in your own code, and demonstrate a live Free Monad-driven tank game.
Supporting code at https://github.com/kenbot/free
Overview of Statistical software such as ODK, surveyCTO,and CSPro
2. Software installation(for computer, and tablet or mobile devices)
3. Create a data entry application
4. Create the data dictionary
5. Create the data entry forms
6. Enter data
7. Add Edits to the Data Entry Application
8. CAPI questions and texts
How AI is Revolutionizing Data Collection.pdfPromptCloud
Artificial Intelligence (AI) is transforming the landscape of data collection, making it more efficient, accurate, and insightful than ever before. With AI, businesses can automate the extraction of vast amounts of data from diverse sources, analyze patterns in real-time, and gain deeper insights with minimal human intervention. This revolution in data collection enables companies to make faster, data-driven decisions, enhance their competitive edge, and unlock new opportunities for growth.
AI-powered tools can handle complex and dynamic web content, adapt to changes in website structures, and even understand the context of data through natural language processing. This means that data collection is not only faster but also more precise, reducing the time and effort required for manual data extraction. Furthermore, AI can process unstructured data, such as social media posts and customer reviews, providing valuable insights into customer sentiment and market trends.
Embrace the future of data collection with AI and stay ahead of the curve. Learn more about how PromptCloud’s AI-driven web scraping solutions can transform your data strategy. https://www.promptcloud.com/contact/
Data analytics is a powerful tool that can transform business decision-making across industries. Contact District 11 Solutions, which specializes in data analytics, to make informed decisions and achieve your business goals.
Introduction to Data Science
1.1 What is Data Science, importance of data science,
1.2 Big data and data Science, the current Scenario,
1.3 Industry Perspective Types of Data: Structured vs. Unstructured Data,
1.4 Quantitative vs. Categorical Data,
1.5 Big Data vs. Little Data, Data science process
1.6 Role of Data Scientist
The Rise of Python in Finance,Automating Trading Strategies: _.pdfRiya Sen
In the dynamic realm of finance, where every second counts, the integration of technology has become indispensable. Aspiring traders and seasoned investors alike are turning to coding as a powerful tool to unlock new avenues of financial success. In this blog, we delve into the world of Python live trading strategies, exploring how coding can be the key to navigating the complexities of the market and securing your path to prosperity.
DESIGN AND DEVELOPMENT OF AUTO OXYGEN CONCENTRATOR WITH SOS ALERT FOR HIKING ...JeevanKp7
Long-term oxygen therapy (LTOT) and novel techniques of evaluating treatment efficacy have enhanced the quality of life and decreased healthcare expenses for COPD patients.
The cost of a pulmonary blood gas test is comparable to the cost of two days of oxygen therapy and the cost of a hospital stay is equivalent to the cost of one month of oxygen therapy, long-term oxygen therapy (LTOT) is a cost-effective technique of treating this disease.
A small number of clinical investigations on LTOT have shown that it improves the quality of life of COPD patients by reducing the loss of their respiratory capacity. A study of 8487 Danish patients found that LTOT for 1524 hours per day extended life expectancy from 1.07 to 1.40 years.
Annex K RBF's The World Game pdf documentSteven McGee
Signals & Telemetry Annex K for RBF's The World Game / Trade Federations / USPTO 13/573,002 Heart Beacon Cycle Time - Space Time Chain meters, metrics, standards. Adaptive Procedural template framework structured data derived from DoD / NATO's system of systems engineering tech framework
41. (r r) r
The Church encoding
of natural numbers is:
r
42. type CNat = forall r. (r -> r) -> r -> r
c0, c1, c2, c3, c4 :: CNat
c0 f z = z
c1 f z = f z
c2 f z = f (f z)
c3 f z = f (f (f z))
c4 f z = f (f (f (f z)))
cSucc :: CNat -> CNat
cSucc cn f = f . cn f
cPlus :: CNat -> CNat -> CNat
cPlus cn1 cn2 f = cn1 f . cn2 f
cMult :: CNat -> CNat -> CNat
cMult cn1 cn2 = cn1 . cn2
43. type CNat = forall r. (r -> r) -> r -> r
c0, c1, c2, c3, c4 :: CNat
c0 f = id
c1 f = f
c2 f = f . f
c3 f = f . f . f
c4 f = f . f . f . f
cSucc :: CNat -> CNat
cSucc cn f = f . cn f
cPlus :: CNat -> CNat -> CNat
cPlus cn1 cn2 f = cn1 f . cn2 f
cMult :: CNat -> CNat -> CNat
cMult cn1 cn2 = cn1 . cn2