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Wolfram U
United States
Приєднався 17 лют 2023
Wolfram U offers free open interactive courses, learning events and other educational resources for professional and technical development. Explore a range of computational fields, build your knowledge of Wolfram Language and get certified by a world-recognized leader in technical innovation.
Get a taste of Wolfram U's content every Monday with new videos on a variety of topics! You can also follow along with our longer courses as we release new lessons every Wednesday and Friday! We are currently exploring statistics through the use of Wolfram Language tools.
Get a taste of Wolfram U's content every Monday with new videos on a variety of topics! You can also follow along with our longer courses as we release new lessons every Wednesday and Friday! We are currently exploring statistics through the use of Wolfram Language tools.
Introduction to Statistics: Computer Simulations
Simulate common statistics experiments with programming! Step-by-step examples show how to determine event independence with a chi-square test and test standard deviation with Wolfram Language functions.
In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statistics and population parameters, confidence intervals, hypothesis testing and normal distributions.
Link to the full playlist: ua-cam.com/play/PLrpSK4Y1vEDPp27kRGHHNWUwbRdTRDspw.html
#wolfram #mathematics #statistics #apstats #data #datascience #dataanalysis #descriptivestatistics #inferentialstatistics
In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statistics and population parameters, confidence intervals, hypothesis testing and normal distributions.
Link to the full playlist: ua-cam.com/play/PLrpSK4Y1vEDPp27kRGHHNWUwbRdTRDspw.html
#wolfram #mathematics #statistics #apstats #data #datascience #dataanalysis #descriptivestatistics #inferentialstatistics
Переглядів: 23
Відео
Introduction to Statistics: Nonparametric Statistics
Переглядів 197 годин тому
Use nonparametric tests when data does not meet t-test conditions (like having a normal distribution). Define and see examples of chi-square, sign and Mann-Whitney U tests. Wilcoxon signed-rank and Spearman rank tests are also discussed. Learn the strengths and weaknesses of nonparametric tests. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data...
Wolfram Notebooks as a Game Engine
Переглядів 4512 годин тому
Build simple 2D side-scrolling platformer video games and play with a controller. Add character sprites and collision detection. Example demos re-create Castlevania, Flappy Bird, Stardew Valley and more. Presenter: Kevin Daily, User Interface Developer, Wolfram Research 0:00 Introduction 2:04 Progress Quest 6:47 Graphics 8:52 Time Advancement 11:47 User Input 15:09 Motion along Each Coordinate ...
Introduction to Statistics: Conditions for Linear Regression
Переглядів 2919 годин тому
Determine when to use linear regression models. Compare requirements for using least-squares regression and Student t distributions. Transform data with logarithms and square roots. Learn how outliers can affect the slope or intercept of lines of best fit. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statist...
Introduction to Statistics: Statistics for Fit Parameters
Переглядів 27День тому
Learn to calculate confidence intervals for slopes and intercepts using residuals and margin of error. Test null and alternative hypotheses with the Student t distribution with two degrees of freedom. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statistics and population parameters, confidence intervals, hyp...
Authoring Documentation for Paclets
Переглядів 62День тому
Document your package's code with the help of built-in tools in Wolfram Language. In this tutorial for beginners, see example documentation pages and learn about the templates for different types of pages. Presenter: Brian Van Vertloo, Document Technology Manager, Wolfram Research 0:00 Outline 0:28 Paclet Documentation History 1:37 Reference Pages 2:58 Guide Pages 3:44 Tech Notes 4:22 Getting S...
Introduction to Statistics: Linear Regression
Переглядів 3914 днів тому
Model quantitative variables' relationship with a least-squares regression line that minimizes the sum of the squared residuals. Define and calculate relevant terms like intercept, slope and r-squared. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statistics and population parameters, confidence intervals, hy...
Introduction to Statistics: Linear Correlation
Переглядів 3414 днів тому
Visualize positive and negative linear correlation as well as uncorrelated data. Calculate, learn about properties of and see how outliers affect correlation coefficients. R-squared and adjusted r-squared statistics are featured; visualize and learn when to use them. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sam...
Continuous Integration & Continuous Deployment of Paclets
Переглядів 9414 днів тому
See examples of continuous integration and deployment (CI/CD) pipelines with Wolfram Language and GitHub. This tutorial for beginners shows workflow automation. Built-in tools help write and run tests. Presenter: Richard Hennigan, Senior Developer, Wolfram Research 0:00 Background and Assumptions 1:03 CI/CD Workflows for Paclets 1:57 Checking 3:49 Creating GitHub Workflows 7:29 Running the Work...
Introduction to Statistics: Analysis of Variance
Переглядів 3221 день тому
Visualize histograms for an example one-way ANOVA problem. Explain the results of the Wolfram Language ANOVA function: an ANOVA table with means, F-ratio and p-value. Calculate and plot the F-ratio. Test for differences in population means by comparing variance between samples with variance within samples using ANOVA tests. In the full course, learn about collecting, describing, analyzing, visu...
Introduction to Statistics: Tests of Homogeneity and Independence
Переглядів 2321 день тому
Perform chi-square tests with two categorical variables. Compare to the chi-square distribution. Learn to calculate degrees of freedom and write null and alternative hypotheses. Test for homogeneity and independence. In the full course, learn about collecting, describing, analyzing, visualizing and interpreting data. Practical examples show sample statistics and population parameters, confidenc...
Wolfram Colloquium Series: Ecological Research with Wolfram Language
Переглядів 10621 день тому
Wolfram Language is used to model and visualize ecosystems, biotic and abiotic processes, nutrient cycles and predator-prey dynamics. Examples show carbon capture and nature-based solutions, food web calculations, combining elephant herd movement with Normalized Difference Vegetation Index (NDVI) and density-area relationships. The researchers present their recent interdisciplinary work combini...
Introduction to Statistics: Conditions for Chi-Square Tests
Переглядів 2828 днів тому
Introduction to Statistics: Conditions for Chi-Square Tests
Introduction to Statistics: Chi-Square Tests
Переглядів 40Місяць тому
Introduction to Statistics: Chi-Square Tests
Get Started Developing Paclets for the Wolfram Paclet Repository
Переглядів 88Місяць тому
Get Started Developing Paclets for the Wolfram Paclet Repository
Introduction to Statistics: Designing Experiments
Переглядів 35Місяць тому
Introduction to Statistics: Designing Experiments
Introduction to Statistics: Observational Studies and Experiments
Переглядів 29Місяць тому
Introduction to Statistics: Observational Studies and Experiments
Using Paclets from the Wolfram Language Paclet Repository
Переглядів 107Місяць тому
Using Paclets from the Wolfram Language Paclet Repository
Introduction to Statistics: Sampling Methods
Переглядів 39Місяць тому
Introduction to Statistics: Sampling Methods
Introduction to Statistics: Collecting Unbiased Data
Переглядів 31Місяць тому
Introduction to Statistics: Collecting Unbiased Data
Wolfram Data Science Boot Camp Alumni Perspectives
Переглядів 110Місяць тому
Wolfram Data Science Boot Camp Alumni Perspectives
Introduction to Statistics: The Multiple Testing Problem
Переглядів 42Місяць тому
Introduction to Statistics: The Multiple Testing Problem
Introduction to Statistics: Hypothesis Tests for Proportions
Переглядів 35Місяць тому
Introduction to Statistics: Hypothesis Tests for Proportions
Wolfram Tools for LLMs (Day 4): Injecting Reliability into Generative AI
Переглядів 212Місяць тому
Wolfram Tools for LLMs (Day 4): Injecting Reliability into Generative AI
Wolfram Tools for LLMs (Day 3): Programmatic Access to LLM Functionality
Переглядів 178Місяць тому
Wolfram Tools for LLMs (Day 3): Programmatic Access to LLM Functionality
Introduction to Statistics: Hypothesis Tests for a Difference of Means
Переглядів 42Місяць тому
Introduction to Statistics: Hypothesis Tests for a Difference of Means
Introduction to Statistics: One- And Two-Sided Hypothesis Tests
Переглядів 41Місяць тому
Introduction to Statistics: One- And Two-Sided Hypothesis Tests
Wolfram Tools for LLMs (Day 2): Chat Notebooks
Переглядів 134Місяць тому
Wolfram Tools for LLMs (Day 2): Chat Notebooks
Wolfram Tools for LLMs (Day 1): Wolfram GPT
Переглядів 2972 місяці тому
Wolfram Tools for LLMs (Day 1): Wolfram GPT
Introduction to Statistics: Computing a P-Value
Переглядів 632 місяці тому
Introduction to Statistics: Computing a P-Value
Nice 🤓
Such a great video. thank you good sir. More economic videos will be amazing. this video was so helpful can't wait too try this later.
i wish to generate audio signals from a stock ticker, can i do that?
Wolfram Language has an integrated FinancialData function (reference.wolfram.com/language/ref/FinancialData.html) and has various Sound functions (reference.wolfram.com/language/guide/SoundAndSonification.html) to get you started. For more help with your specific project, you can post your code and any questions you have about it on Wolfram Community (community.wolfram.com/).
which software are you using to run this program?
Hi! The presenter is using Wolfram Language in Mathematica. You can try it for free here: www.wolfram.com/mathematica/trial/
@@wolframu thank you
I am trying to understand if indeed there truly has been an alteration of the path of the eclipse. I need to know right now so I’m unab😢le to listen to your vid. No one seems to be commenting on the April 1 Fools Day Joke about the new map. Somesay yes, others no, there is no new path. Please, how could NASA make such a HUGE mistake?
It's because they started CEARN and it has moved the earth. Cearn is trying to destroy earth😢
That is incredible. Thank you for this unique presentation, sir.
Glad you enjoyed it!
@wolframu I really did, through the video it was increasingly impressive.
Is the notebook available? Thanks.
The notebook will be available shortly! We will post a link here when it is available.
The notebook is available from the Wolfram Tech Conference website: www.wolfram.com/events/technology-conference/2023/presentations/
@@wolframu Thanks.
Yeah, but how do you getit?
You can access the plugin through a "Get Wolfram GPT" link on this page: www.wolfram.com/wolfram-plugin-chatgpt/
Great. Thanks. And thanks for posting this on UA-cam...
You're welcome! Be sure to check upcoming events on the Wolfram Events Page: events.wolfram.com
Nice!
Thanks for your feedback! Be sure to check upcoming events on the Wolfram Events Page: events.wolfram.com
It would be great to have the notebook to download.
You can access the notebook on the course page: www.wolfram.com/wolfram-u/courses/programming-applications/video-games-in-wolfram-language-dev031/
@@wolframu Thanks.
GPTs (and almost all transformers, in fact all deep learning models) are statistical models, so they answers are statistical probabilities, hence randomness is built-in there is no escape.
Yes! Thank you for your comment. Be sure to check upcoming events on the Wolfram Events Page: events.wolfram.com
It is nice to compare your product with others, but it is not nice to dump on open source projects. In python students really learn machine learning (and deep learning) being open source, code is workable and understandable and one can learn by changing a lot of things, this can't be said for Mathematica that abstracts everything, also, if abstraction is required (easy and faster development) then keras for tensorflow and lightening for pytorch are good choice. I love mathematica, and I love mathematica for easy math syntax and graphics, I think they are the best (and easy, compared to any open source language) but since mathematica is closed source I don't really understand it much, I only use it for mathematics and graphing equations or system of equations (or simulations with systemmodeler).
please make a vedio on optoion derivative pricing, dynamichedgeing backtesting. any financial derivative pricing model
It may not be as specific as you're looking for, but we do have some financial and financial modeling courses available in the Wolfram U catalog: www.wolfram.com/wolfram-u/courses/finance/ We're currently working on expanding our financial modeling course offerings too!
8:19 wow, is the chat engine running locally or does it communicate with wolfram servers, can it work without internet? what are system requirements for this? what is context length, what languages does it support or is it english only?
Looked it up, but realised you were going to mention models (choice) so modified question now, can I use ollama or llamacpp models, or just any model running on a server and integrate it with mathematica?
Right now, we support models from the following providers: OpenAI, Anthropic, PaLM, GoogleSpeech, and ElevenLabs We do not support other models yet, but we are planning to add a feature allowing users to define their own service connection that they can use with any of our LLMFunctions and Chat Notebooks.
I upgraded straight from 12, skipped 13. But I only got engine not complete mathematica, though I've integrated it with jupyter.
Great lecture!
Glad it was helpful!
May you please do video on dotplots
We don't have a video specifically on dot plots in this course, but they are similar to histograms. We have a series of videos on histograms later in this course.
Uncertainty inside system models is huge. I hope you guys continue with that kind of functionality
Will do. Thanks for your support! Check our upcoming events: events.wolfram.com
Hello. How can I calculate the p value and convert it to hexadecimal format? Is it different for every bitcoin address? For example: p = 0xFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFEBAAEDCE6AF48A03BBFD25E8CD0364141
Don't know why but I m liking these explanation. Btw what is this software.
This video demonstrates Wolfram Language! You can try it for free on the Wolfram Cloud here: www.wolfram.com/cloud/
Nice explanation,good video
This is a really good example of what you can do with the Wolfram Language. Thanks!
How about we get to the title! Solving math problems
Thank you for this. Is the example notebook saved anywhere publicly available?
You can get the notebooks from the course page: www.wolfram.com/wolfram-u/courses/programming-applications/wolfram-language-for-python-users-dev925/
Thx
Thank you...
❤
BRAVO!!! I would highligth the "compiling the compiler" advance. And also the tech advancing process of "compiling a function and then injecting into wolfram interface" for using while coding, This resembles very well what natural physics and natural life forms are doing: Working by the dynamics of "second order differential equations". We, as humanity, are going exactly trough that process in an umprecedented threshold with AI, Now, as we work so tightly with it bettering it and also bettering human though (trough NeuraLevels neuroservices, for example), we have entered the Hybrid Artificial Intelligence Era, and it is a "second order differential equation" type of process, just as Mr. McLoone presented. We have hopes... and now all the tools needed to do it GREAT!
Great integration of ChatGPT and the Wolfram stack … Thanks …Syd Geraghty
Thank you.
Incredible how quickly the Wolfram universe has adapted to and completed LLMs. They are two pieces of the same puzzle. Jon's presentation is as usual brilliant and concrete. A new world is emerging.
You did very well Wolfram, but sometime I do a text summarize task which I dont need to put in Wolfram but GPT4 still make it complex and It's not closed to the answer I want Maybe I should change the promt
Why not show result with gpt 4
Unfortunately Jon did not yet have access to GPT 4 when he gave this talk. 😊 But he says, "While GPT-4 will no doubt do better on the 'weaknesses' examples, it will just be pushing the failure a bit further away. The principles will still remain the same."
I am pleased to share with Professionals and Companies the most advanced technological tool in existence: the Digital Twin that I invented in 1981 under the name of Virtual Instruments. ua-cam.com/video/eadaQiL_AK0/v-deo.html ua-cam.com/video/fXlp4QLdWQs/v-deo.html Export the Copilot, Chat GPT, Revit, Plant 3D, Civil 3D, Inventor, Engi file of the Building or Refinery to Excel, prepare Budget 1 and export it to COBRA. Prepare Budget 2 and export it to Microsoft Project. Solve the problems of Overallocated Resources, Planning Problems, prepare the Budget 3 with which the construction of the Building or the Refinery is going to be quoted.
Always nice to hear a Saxonian speaking English.
The big problem is that even if Wolfram can do something, chatGPT often can't figure out the right syntax to do it. Probably there were not nearly enough samples in the training data so that it knows how to correctly interact with Wolfram Alpha / Language. Simple example: "Give me a bar chart of the 10 most valuable currencies in the world." It fails. If you instead use the browsing mode and ask: "Generate Python code for a bar chart of the 10 most valuable currencies in the world." you get exactly what you want. Also, I feel like some of the data in Wolfram are really out of date like month-over-month inflation data hasn't been updated in over a year, as far as I can see. This is very old compared to data you can get through a simple Google search nowadays. So it is really not clear to me if data is a strength of Wolfram, compared to all of the internet that chatGPT can access with the browsing mode.
You can fix this by running GPT in a loop and getting it to respond to its own errors.
Thanks
In a few months it will become the best matemathician ever.