Y'all are not constructing multi-class labeling correctly....
@ElizabethOliver-n1dКүн бұрын
I'm favoured financially with Bitcoin ETFs, Thank you buddy. $43,700 biweekly profit regardless of how bad it gets on the economy!!!...
@LucasBenjamin-n2yКүн бұрын
Huge! been trying to trade on my own for a while now but it isn’t going well. Few weeks ago I lost about $7,000 in a particular trade. Can you at least advise me on what to do?
@ElizabethOliver-n1dКүн бұрын
Well, I picked the challenge to put my finances in order. Then I invested in cryptocurrency, stocks, through the assistance of my discretionary fund manager,
@ElizabethOliver-n1dКүн бұрын
Mr Alex brucemacias
@AndySullivan-f5oКүн бұрын
I'm not here to converse for him to testify just for what I'm sure of, he's trust worthy and best option ever seen
@EberePromise-g1kКүн бұрын
Such a genuine personality!! He is really a good investment advisor. I was privileged to attend some of his seminars.
@ahmedkhaled330Күн бұрын
fantastic talk. slides and references, please?
@kapilkhond6339Күн бұрын
This was really helpful session. Thanks for sharing such insights here.
@emmang2010Күн бұрын
Thank you very much.
@Ale-lq2qk2 күн бұрын
starts at 3:30
@MrBigbanan2 күн бұрын
⋯⋰⋮⩓⫶⫻
@marc-andrechenier54882 күн бұрын
What not use linearmodels for python? It also has fast treatment of fixed effects and can be used for e.g. two-way fixed effects applications
@s3alfisc2 күн бұрын
Hi - pyfixest author here. linearmodels is a great library - I simply like R's fixest library very much!
@marc-andrechenier54882 күн бұрын
@@s3alfisc Thanks for the response, definitely curious about trying out your library at work :)
@s3alfisc2 күн бұрын
@@marc-andrechenier5488 Cool, looking forward to any potential feedback! =)
@sefumbweha99262 күн бұрын
Since October 7 the way Hamas been moving ther thing just making the future in Palestine harder. say peace na fit it anymore. Instead of talk, its violence all the time, and the zionest entity takes advantage. The last hope was wit Salam Fayyad who could play the games. Hamas instead of looking after the everyday people just get rich in Doha, spend money on tunnels and luxury
@TheNitroPython2 күн бұрын
You should post the GitHub repo link
@6Diego1Diego92 күн бұрын
he wont open source this hypothetical new framework? sad
@MischaPanch2 күн бұрын
I might actually do it soon since there'd be at least two users I know of (more than zero), but it will probably be very difficult to grow a community around it
@MorrisonOscar-u6l4 күн бұрын
Anderson Jessica Jackson Timothy Martinez Helen
@Mayur7Garg4 күн бұрын
The quality of the video is too poor. The text in the notebook is barely readable.
@TheKumarAshwin4 күн бұрын
Pandas Left the chat
@mrchesitostar76525 күн бұрын
Hi Bro this Is amazing appreciate it
@yssefunc5 күн бұрын
Nice and clean talks … love it
@KatherineCoursey-d5q5 күн бұрын
Moore Deborah Gonzalez Daniel Martin Thomas
@KatherineCoursey-d5q5 күн бұрын
Wilson Eric Thomas Kevin Lopez Christopher
@KatherineCoursey-d5q5 күн бұрын
Harris Cynthia Perez Betty Martinez Thomas
@KatherineCoursey-d5q5 күн бұрын
Moore Jason Young Linda Johnson Jason
@DuBoisEdmund-r1t6 күн бұрын
White David Garcia Angela White Steven
@DuBoisEdmund-r1t6 күн бұрын
Thompson Larry Anderson Betty Jones Paul
@DuBoisEdmund-r1t6 күн бұрын
Smith Christopher Martin Dorothy Lopez Jose
@hannahrussel23297 күн бұрын
Young Matthew Lewis Robert Brown Margaret
@MelanieKnudsen-y4b7 күн бұрын
Wilson Timothy White Steven Anderson Donald
@jiayangcheng9 күн бұрын
Love the presentation. Great work!
@АкулинаСемерикова9 күн бұрын
Smith Charles Brown Brenda Martinez Melissa
@CherryBlossomStorm11 күн бұрын
but if I make a diagram, how do I know its the correct diagram, without having run experiments? you have your diagram first then do your modeling and analysis! I suppose you have to start with some hypothesis though
@viorelteodorescu11 күн бұрын
Sounds very good - and what I needed at this point in my developing a solution for document management. Thank you for the software and for the lecture! Will try it straight away.
@mubangizijulius430311 күн бұрын
This is the best video i have ever found online.do you have other good videos like this
@jackpurdoneverydayzero12 күн бұрын
Amazing how NLP has changed with the release of ChatGPT etc
@EdnaJohansson-c4e12 күн бұрын
Alia Shoals
@ish69414 күн бұрын
This is super cool!
@donciclon14 күн бұрын
Love his talks, but damn, had to watch this at .7x speed
@MargaretWilson-h9c15 күн бұрын
Wisozk Turnpike
@vunder873715 күн бұрын
This truly was a wonderful presenter, would love to listen to him on other presentations
@BeckCaesar-r8l15 күн бұрын
Taylor Nancy Martin Ruth Gonzalez Daniel
@BeckCaesar-r8l15 күн бұрын
Davis Timothy Anderson Michael White Donna
@orasporas115 күн бұрын
The font is to small.
@noclaf7816 күн бұрын
Well presented!
@RodneyVillegas-o8k16 күн бұрын
Harris Melissa Johnson Mary Walker Carol
@metecantimur954217 күн бұрын
@19:35, I think we can implement the __call__ function to return the value of the polynomial for value x.
@taxzanUSA17 күн бұрын
I want to scrape multiple tables from a website search query into Excel. where do i begin?
@wolpumba409917 күн бұрын
*cudf.pandas: Accelerating Pandas with GPUs for Faster Data Processing* * *0:00** Introduction:* Ashwin Srinath, Senior Software Engineer at NVIDIA, introduces cudf.pandas, a tool that allows you to run pandas code on GPUs without code changes, achieving significant speedups. * *0:10** Motivation:* Pandas is popular but can be slow due to single-threading and its non-query-engine nature. Alternatives like cuDF exist, but they often require code changes and have different APIs. * *2:08** cuDF Overview:* cuDF, based on CUDA and C++, is a GPU-based data frame library offering a pandas-like API and substantial performance gains (10-100x faster than pandas). It currently supports 60-75% of the pandas API. * *3:25** Reasons to Stick with Pandas:* Despite alternatives, pandas remains valuable for its flexibility, ease of collaboration, a vast ecosystem of dependent libraries, and ongoing performance improvements. * *5:15** cudf.pandas Approach:* cudf.pandas aims to combine the benefits of pandas with GPU acceleration, allowing users to retain the familiar pandas API while leveraging the speed of GPUs. * *5:34** How It Works:* cudf.pandas acts as a proxy for pandas, intercepting pandas calls and attempting to execute them on the GPU via cuDF. If an operation isn't supported on the GPU, it seamlessly falls back to CPU execution using pandas. * *7:54** Demo (Part 1 - Basic Operations):* The demo showcases how to load the cudf.pandas extension in Jupyter Notebook. Several examples demonstrate performance gains for groupby, string operations, and merge operations, but also highlights cases where GPU acceleration doesn't provide a speedup (e.g., `count` on axis=1). * *10:53** Proxy Pattern Explained:* cudf.pandas uses a proxy pattern where proxy functions and types intercept pandas calls, attempting GPU execution first and falling back to CPU if necessary. * *11:18** Demo (Part 2 - Performance Optimization):* The demo focuses on optimizing time series data operations. Using the cudf.pandas profiler reveals that `index.between_time` is a CPU bottleneck. By rewriting the code to use GPU-supported datetime properties, the execution time is significantly reduced. * *15:11** Optimization Benefits:* Code optimized for GPU execution often also runs faster on the CPU, demonstrating that writing GPU-friendly code can be beneficial even without a GPU. * *15:49** Demo (Part 3 - Third-Party Library Acceleration):* The demo shows how cudf.pandas can accelerate third-party libraries that rely on pandas. Using LangChain as an example, it demonstrates how an LLM-powered agent utilizing pandas for data analysis can benefit from GPU acceleration, significantly reducing query execution time. * *19:00** Recap:* cudf.pandas offers GPU acceleration for pandas with no code changes. Optimizing code for GPU execution is crucial for maximum performance. Third-party libraries can leverage GPUs through cudf.pandas. * *19:28** How It Works (Technical Details):* cudf.pandas relies on the proxy pattern and customizes the Python import mechanism to deliver proxy modules, ensuring seamless integration with existing pandas code. * *20:50** Comparison with Other Approaches:* The talk briefly discusses the limitations of duct typing and the potential of the DataFrame Standard API for interoperability between data frame libraries. * *22:42** FAQs:* The presentation concludes with FAQs covering performance expectations, pandas API support, compatibility with third-party libraries, and handling data larger than GPU memory. * *24:03** Getting Started:* Instructions for installation and access to demo materials are provided. * *24:34** Q&A:* A brief Q&A session addresses questions from the audience regarding CPU performance gains, multi-node scaling, Docker images, UDF support, and the availability of the GitHub repository. I used gemini-1.5-pro-exp-0801 on rocketrecap dot com to summarize the transcript. Cost (if I didn't use the free tier): $0.09 Input tokens: 23132 Output tokens: 856
@UlyssesAlger-k5l17 күн бұрын
2017 Stephon Cliff
@visskiss18 күн бұрын
Hi Dimitry, I am trying to discover how to get a "minimum heart rate" from a bunch of samples of "sedentary heart rate" say about 10 per hour. The minimum heart rate would express the true minimum for the (noisy) samples (as opposed to just actual minimum). I thought about using extreme value analysis, but after this explanation, that doesn't seem correct. What would you suggest?
@DreamsAPI18 күн бұрын
Thank you Vincent for sharing the link to this video of yours mentioning contextual helper in Jupyter lab notebook. Plus your demo of reflection is a good idea was extra goodie on top
@StuckDuckF19 күн бұрын
Great work, thank you for your efforts.
@duncanhart19 күн бұрын
Those people who keep talking throughout the presentation are incredibly rude.
@OOD202119 күн бұрын
The slides are great but did anybody find out where this guy was talking about?