Explore detailed Topic Modeling via LDA Laten Dirichlet Allocation and their steps.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Dynamic Programming is an algorithmic paradigm that solves a given complex problem by breaking it into subproblems and stores the results of subproblems to avoid computing the same results again.
Explore detailed Topic Modeling via LDA Laten Dirichlet Allocation and their steps.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Dynamic Programming is an algorithmic paradigm that solves a given complex problem by breaking it into subproblems and stores the results of subproblems to avoid computing the same results again.
This lecture slide contains:
1. Regular Languages
2. Regular Operations
3. Closure of regular languages
4. Regular expression
5. Precedence of regular operations
6. RE for different languages
7. RE to NFA conversion
8. DFA to GNFA to RE conversion
A short presentation to share knowledge about topic Decidability of Theory of Automata Course.
To make people to be aware how to know which formal languages are decidable and why...!
Indexing is used to speed up access to desired data.
E.g. author catalog in library
A search key is an attribute or set of attributes used to look up records in a file. Unrelated to keys in the db schema.
An index file consists of records called index entries.
An index entry for key k may consist of
An actual data record (with search key value k)
A pair (k, rid) where rid is a pointer to the actual data record
A pair (k, bid) where bid is a pointer to a bucket of record pointers
Index files are typically much smaller than the original file if the actual data records are in a separate file.
If the index contains the data records, there is a single file with a special organization.
Given two integer arrays val[0...n-1] and wt[0...n-1] that represents values and weights associated with n items respectively. Find out the maximum value subset of val[] such that sum of the weights of this subset is smaller than or equal to knapsack capacity W. Here the BRANCH AND BOUND ALGORITHM is discussed .
After a long period, I bring you new - fresh Presentation which gives you a brief idea on sub-problem of Dynamic Programming which is called as -"Longest Common Subsequence".I hope this presentation may help to all my viewers....
This lecture slide contains:
1. Regular Languages
2. Regular Operations
3. Closure of regular languages
4. Regular expression
5. Precedence of regular operations
6. RE for different languages
7. RE to NFA conversion
8. DFA to GNFA to RE conversion
A short presentation to share knowledge about topic Decidability of Theory of Automata Course.
To make people to be aware how to know which formal languages are decidable and why...!
Indexing is used to speed up access to desired data.
E.g. author catalog in library
A search key is an attribute or set of attributes used to look up records in a file. Unrelated to keys in the db schema.
An index file consists of records called index entries.
An index entry for key k may consist of
An actual data record (with search key value k)
A pair (k, rid) where rid is a pointer to the actual data record
A pair (k, bid) where bid is a pointer to a bucket of record pointers
Index files are typically much smaller than the original file if the actual data records are in a separate file.
If the index contains the data records, there is a single file with a special organization.
Given two integer arrays val[0...n-1] and wt[0...n-1] that represents values and weights associated with n items respectively. Find out the maximum value subset of val[] such that sum of the weights of this subset is smaller than or equal to knapsack capacity W. Here the BRANCH AND BOUND ALGORITHM is discussed .
After a long period, I bring you new - fresh Presentation which gives you a brief idea on sub-problem of Dynamic Programming which is called as -"Longest Common Subsequence".I hope this presentation may help to all my viewers....
Prolog, Prolog Programming IN AI. Prolog is an Artificial Intelligence programming language. Prolog is a logic programming language associated with artificial intelligence and computational linguistics. Its applications include natural language understanding and expert systems. Prolog is notably a so-called nonprocedural, or declarative, language.
I am kind of confused about quantifiers. I am not sure how to transl.pdfAMITPANCHAL154
I am kind of confused about quantifiers. I am not sure how to translate them into english
correctly so a quick Guide to how or the answer will work. Thanks!
***** (A = universal) , (E = existential), (V = or), (^ = and) I do not know how to input the real
symbol)
1.) AxAyAz([x+y]+z = x+([y+z])
2.) Here x, y are students C(x) is having a computer and F(x,y) indicates that x and y are friends.
Ax(C(x) vEy[C(y)^F(x,y)]
3.) Suppose that x and y are real numbers
a. AxAy([x>0 ^ y>0] ------> [x+y>0])
b. AxAy([x<0 ^ 4<0] [x(y)>0])
Solution
There are several logical symbols in the alphabet, which vary by author but usually
include: The quantifier symbols and The logical connectives: for conjunction, for disjunction, for
implication, for biconditional, for negation. Occasionally other logical connective symbols are
included. Some authors use , or Cpq, instead of , and , or Epq, instead of , especially in contexts
where is used for other purposes. Moreover, the horseshoe may replace ; the triple-bar may
replace , and a tilde (~), Np, or Fpq, may replace ; ||, or Apq may replace ; and &, or Kpq, may
replace , especially if these symbols are not available for technical reasons. Parentheses,
brackets, and other punctuation symbols. The choice of such symbols varies depending on
context. An infinite set of variables, often denoted by lowercase letters at the end of the alphabet
x, y, z, … . Subscripts are often used to distinguish variables: x0, x1, x2, … . An equality symbol
(sometimes, identity symbol) =; see the section on equality below. It should be noted that not all
of these symbols are required - only one of the quantifiers, negation and conjunction, variables,
brackets and equality suffice. There are numerous minor variations that may define additional
logical symbols: Sometimes the truth constants T, Vpq, or , for \"true\" and F, Opq, or , for
\"false\" are included. Without any such logical operators of valence 0, these two constants can
only be expressed using quantifiers. Sometimes additional logical connectives are included, such
as the Sheffer stroke, Dpq (NAND), and exclusive or, Jpq. [edit]Non-logical symbols The non-
logical symbols represent predicates (relations), functions and constants on the domain of
discourse. It used to be standard practice to use a fixed, infinite set of non-logical symbols for all
purposes. A more recent practice is to use different non-logical symbols according to the
application one has in mind. Therefore it has become necessary to name the set of all non-logical
symbols used in a particular application. This choice is made via a signature.[2] The traditional
approach is to have only one, infinite, set of non-logical symbols (one signature) for all
applications. Consequently, under the traditional approach there is only one language of first-
order logic.[3] This approach is still common, especially in philosophically oriented books. For
every integer n = 0 there is a collection of n-ary, or n-place, predicate .
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
3. Recursive definitions A predicate is recursively defined if one or more rules in its definition refers to itself. Ex: is_digesting(X,Y) :- just_ate(X,Y). is_digesting(X,Y) :- just_ate(X,Z), is_digesting(Z,Y). just_ate(mosquito,blood(john)). just_ate(frog,mosquito). just_ate(stork,frog). It's just a knowledge base containing two facts and two rules. But the definition of the is_digesting/2 predicate is recursive.
4.
5. Clause ordering, goal ordering, and termination Consider the following ex: child(martha,charlotte). child(charlotte,caroline). child(caroline,laura). child(laura,rose). descend(X,Y) :- child(X,Y). descend(X,Y) :- child(X,Z), descend(Z,Y). We'll make two changes to it, and call the result descend2.pl: child(martha,charlotte). child(charlotte,caroline). child(caroline,laura). child(laura,rose). descend(X,Y) :- descend(Z,Y), child(X,Z). descend(X,Y) :- child(X,Y).
6. we have merely reversed the order of the two rules, and reversed the order of the two goals in the recursive clause. So, viewed as a purely logical definition, nothing has changed. But the procedural meaning has changed dramatically. For example, if you pose the query descend(martha,rose). you will get an error message (`out of local stack', or something similar). Because descend1.pl and descend2.pl are Prolog knowledge bases with the same declarative meaning but different procedural meanings: from a purely logical perspective they are identical, but they behave very differently.
7. The declarative and procedural meanings of a Prolog program can differ, when writing Prolog programs you need to bear both aspects in mind. When you need to think about how Prolog will actually evaluate queries. The following questions must be considered: Are the rule orderings sensible? How will the program actually run?
8. Lists lists, an important recursive data structure widely used in computational linguistics. It is a finite sequence of elements. Here are some examples of lists in Prolog: [mia, vincent, jules, yolanda] [mia, robber(honey_bunny), X, 2, mia] [] [mia, [vincent, jules], [butch, girlfriend(butch)]] [[], dead(zed), [2, [b, chopper]], [], Z, [2, [b, chopper]]]
9. Lists We can specify lists in Prolog by enclosing the elements of the list in square brackets(that is, the symbols [ and ]). The elements are separated by commas. All sorts of Prolog objects can be elements of a list and the same item may occur more than once in the same list. The empty list(as its name suggests) is the list that contains no elements. lists can contain other lists as elements. Any non-empty list can be thought of as consisting of two parts: the head and the tail. The head is simply the first item in the list; the tail is everything else.
10. Members Member is a fundamental Prolog tool for manipulating lists, and to introduce the idea of recursing down lists. consider a program that, when given as inputs an arbitrary object X and a list L, tells us whether or not X belongs to L. The program that does this is usually called member. Here it is: member(X,[X|T]). member(X,[H|T]) :- member(X,T). one fact (namely member(X,[X|T])) and one rule (namely member(X,[H|T]) :- member(X,T)). But note that the rule is recursive (after all, the functor member occurs in both the rule's head and tail)
11. Members Suppose we posed the following query: ? -member(yolanda,[yolanda,trudy,vincent,jules]). Prolog will immediately answer `Yes'. Because it can unify yolanda with both occurrences of X in the first clause (the fact) in the definition of member/2, so it succeeds immediately.
12. Recursing Down Lists Member works by recursively working down a list, doing something to the head, and then recursively doing the same thing to the tail. Recursing down a list (or indeed, several lists) in this way is extremely common in Prolog. When working with lists, we often want to compare one list with another, or to copy bits of one list into another, or to translate the contents of one list into another, or something similar. Ex: Let's suppose we need a predicate a2b/2 that takes two lists as arguments, and succeeds if the first argument is a list of as, and the second argument is a list of bs of exactly the same length. If we pose the following query a2b([a,a,a,a],[b,b,b,b]). we want Prolog to say `yes'.
13. Recursing Down Lists If we pose the query a2b([a,a,a,a],[b,b,b]) or the query a2b([a,c,a,a],[b,b,5,4]). we want Prolog to say `no'. For longer lists, think recursively. So when should a2b/2 decide that two non-empty lists are a list of as and a list of bs of exactly the same length?
14. Simple: when the head of the first list is an a, and the head of the second list is a b, and a2b/2 decides that the two tails are lists of as and bs of exactly the same length! This immediately gives us the following rule: a2b([a|Ta],[b|Tb]) :- a2b(Ta,Tb). The a2b/2 predicate should succeed if its first argument is a list with head a, its second argument is a list with head b, and a2b/2 succeeds on the two tails. Now, this definition make good sense declaratively.
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