GeostatsGuy Lectures
GeostatsGuy Lectures
  • Видео 173
  • Просмотров 894 081
09 Data Science Interactive: Monte Carlo Simulation
Data Science Interactive Python Demonstrations: Chapter 09: Monte Carlo Simulation
In this walk-through, I explain the basics of Monte Carlo Simulation (MCS). Essential for:
* doing math with distributions to build uncertainty models
* bootstrap for machine learning model bagging and random forest
* Markov chain Monte Carlo for Bayesian regression, etc.
Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories github.com/GeostatsGuy/Python... . For more complete lectures check out my other RUclips lectures with linked Python workflows and demonstrations:
* Monte Carlo Simulation:
ruclips.net/video/Qb8TsSINpnU/видео.html
* Bootstrap:
ruclips.net/video...
Просмотров: 1 232

Видео

08 Data Science Interactive: Central Limit Theorem
Просмотров 6967 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 08: Central Limit Theorem In this walk-through, I explain the central limit theorem. If you work with averaging or summations of random variables then you will encounter the central limit theorem in you data science workflows! Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories github.com...
07 Data Science Interactive: Correlation Coefficients with Outliers
Просмотров 6517 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 07: Correlation Coefficients with Outliers In this walk-through, I explain the concept of correlation for machine learning feature engineering and focus on the limitation of sensitivity to outliers. This then motivates the introduction to the rank correlation coefficient and a comparison between both regular correlation coefficient and ran...
06 Data Science Interactive: Correlation Coefficients
Просмотров 7237 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 06: Correlation Coefficients In this walk-through, I explain the concept of correlation for machine learning feature engineering. Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories @ github.com/GeostatsGuy/PythonNumericalDemos/blob/master/Interactive_Correlation_Coefficient.ipynb . For m...
05 Data Science Interactive: Distribution Transformation for Machine Learning Feature Engineering
Просмотров 7168 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 05: Distribution Transformation for Machine Learning Feature Engineering In this walk-through, I explain the concept of distribution transformation for machine learning feature engineering. Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories @ github.com/GeostatsGuy/PythonNumericalDemos/b...
04 Data Science Interactive: Norms for Machine Learning
Просмотров 6698 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 04: Norms for Machine Learning In this walk-through, I explain the concept of norms for predictive machine learning and then demonstrate the impact of choice of norm on a simple predictive machine learning model, linear regression. Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories @ git...
03 Data Science Interactive: Bayesian Coin Example
Просмотров 6938 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 03: Bayesian Coin Example In this walk-through I demonstrate the Bayesian coin example from Sivia's Bayesian Tutorial (1996, 2006). I use this example in my courses, because I found it very useful to help my students to understand Bayesian updating. I hope that it helps you also! Follow along with the interactive Python code in a Jupyter N...
02 Data Science Interactive: Bayesian Updating
Просмотров 1,3 тыс.8 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 02: Bayesian Updating In this walk-through I demonstrate the basic concepts of Bayesian updating for the case of what is the probability of a thing happening given a positive test with an interactive dashboard and custom plots. Then I show the example of Bayesian updating under the assumption of Gaussian distributed Follow along with the i...
01 Data Science Interactive: Marginal, Joint, Conditional
Просмотров 2,6 тыс.8 месяцев назад
Data Science Interactive Python Demonstrations: Chapter 01: Marginal, Joint and Conditional Probabilities and Distributions In this walk-through I demonstrate the basic concepts of marginal, joint and conditional probabilities and distributions with a simple synthetic mineral mining dataset. Follow along with the interactive Python code in a Jupyter Notebook available in my GitHub repositories ...
16c Data Analytics: Decision Making
Просмотров 2,2 тыс.Год назад
Lecture on decision making in the presence of uncertainty. Follow along with the demonstration workflow in Python: o. Decision making, optimum estimation in the presence of uncertainty: github.com/GeostatsGuy/PythonNumericalDemos/blob/master/Interactive_DecisionMaking.ipynb Follow along with the demonstration workflow in Excel: o. Decision making, optimum estimation in the presence of uncertain...
Data Science Basics: Bootstrap
Просмотров 2,6 тыс.2 года назад
Live Jupyter walk-through of bootstrap for uncertainty modeling in Python. I demonstrate that we can bootstrap to calculate uncertainty, due to data paucity, for any statistic! This should be enough to get anyone started building data analytics workflows in Python. The demonstrated workflow is available at: github.com/GeostatsGuy/PythonNumericalDemos/blob/master/PythonDataBasics_Bootstrap.ipynb...
Data Science Basics: Bivariate Data Visualization
Просмотров 1,6 тыс.2 года назад
Live Jupyter walk-through of basic bivariate data visualization in Python with the matplotlib and Seaborn package. I start from a simple scatter plot and incrementally add complexity with attention to design and composition of plotting elements for improved communication. This should be enough to get anyone started building data analytics workflows in Python. The demonstrated workflow is availa...
Data Science Basics: Univariate Statistics
Просмотров 1,7 тыс.3 года назад
Live Jupyter walk-through of basic univariate statistics in Python.This should be enough to get anyone started building predictive machine learning workflows in Python. The demonstrated workflow is available at: github.com/GeostatsGuy/PythonNumericalDemos/blob/master/PythonDataBasics_Univariate_Statistics.ipynb #DataAnalytics #DataVisualization #DataScience #Statistics
Data Science Basics: Predictive Machine Learning
Просмотров 1,8 тыс.3 года назад
Live Jupyter walk-through of basic predictive machine learning model building in Python with the scikit-learn package.This should be enough to get anyone started building predictive machine learning workflows in Python. The demonstrated workflow is available at: github.com/GeostatsGuy/PythonNumericalDemos/blob/master/PythonDataBasics_PedictiveMachineLearning.ipynb #DataAnalytics #DataVisualizat...
DIRECT 2021 14 Tuning Deep Learning Models Maldonado-Cruz
Просмотров 4633 года назад
DIRECT Consortium at The University of Texas at Austin, working on novel methods and workflows in spatial, subsurface data analytics, geostatistics and machine learning. This is Tuning Ensemble Machine Learning Uncertainty Models by Eduardo Maldonado-Cruz. Join the consortium for access to all graduate student research, papers, codes and demonstration workflows.
DIRECT 2021 10 Deep Learning Multi-scale Modeling
Просмотров 4243 года назад
DIRECT 2021 10 Deep Learning Multi-scale Modeling
DIRECT 2021 11 Machine Learning History Matching
Просмотров 4453 года назад
DIRECT 2021 11 Machine Learning History Matching
DIRECT 2021 12 Scientific Machine Learning
Просмотров 2923 года назад
DIRECT 2021 12 Scientific Machine Learning
DIRECT 2021 13 Multi-scale Neural Networks Santos
Просмотров 5713 года назад
DIRECT 2021 13 Multi-scale Neural Networks Santos
DIRECT 2021 09 Spatial Variogram via CNN
Просмотров 5733 года назад
DIRECT 2021 09 Spatial Variogram via CNN
DIRECT 2021 08 Spatial Statistics for Modeling
Просмотров 3653 года назад
DIRECT 2021 08 Spatial Statistics for Modeling
DIRECT 2021 06 Machine Learning Spatial Bias Mitigation
Просмотров 2213 года назад
DIRECT 2021 06 Machine Learning Spatial Bias Mitigation
DIRECT 2021 07 CRM for scikit-learn Estimator
Просмотров 1783 года назад
DIRECT 2021 07 CRM for scikit-learn Estimator
DIRECT 2021 05 ML Well Correlation
Просмотров 4873 года назад
DIRECT 2021 05 ML Well Correlation
DIRECT 2021 04 Spatial Data Analytics
Просмотров 3723 года назад
DIRECT 2021 04 Spatial Data Analytics
DIRECT 2021 01 Introduction
Просмотров 8163 года назад
DIRECT 2021 01 Introduction
DIRECT 2021 02 Dynamic Time Warping
Просмотров 4393 года назад
DIRECT 2021 02 Dynamic Time Warping
Data Science Basics: Pipelines
Просмотров 1,9 тыс.3 года назад
Data Science Basics: Pipelines
Texas Groundwater Uncertainty Keynote July, 2021
Просмотров 7813 года назад
Texas Groundwater Uncertainty Keynote July, 2021
5f Machine Learning: Non-cooperative Game Theory
Просмотров 1,5 тыс.3 года назад
5f Machine Learning: Non-cooperative Game Theory

Комментарии

  • @nhattruong8691
    @nhattruong8691 7 дней назад

    Awesome video, Thanks! If we have a problem with ML, could we discuss the issue with you?

  • @jeinffersonjbg
    @jeinffersonjbg 7 дней назад

    I love it

  • @frankyates1
    @frankyates1 28 дней назад

    One of the best introductory classes I’ve seen, thanks so much. I have a basic (sorry) technical question: you seem to be showing slides from a ppt but inside you have working python notebook. How do you do this?

  • @pgdelafuente
    @pgdelafuente Месяц назад

    do you have a video of spatial correlation/auto correlation?

  • @MillerMoore-gq2pe
    @MillerMoore-gq2pe 2 месяца назад

    Cool video

  • @BalaMurugan-lp8ef
    @BalaMurugan-lp8ef 2 месяца назад

    Hi sir , could you please interpret the result ? , i am getting some confusion related to the categorical value interpretation from the output

  • @joabe1207
    @joabe1207 2 месяца назад

    Your classes are amazing!

  • @tacitvision9541
    @tacitvision9541 2 месяца назад

    Thanks! Played with your code for the Gaussian stuff and had an ah-ha moment.

  • @prydt
    @prydt 2 месяца назад

    Great explanation!!

  • @doms962
    @doms962 2 месяца назад

    Let's say that I'm tracking the profile of some person. I choose features F1, F2, F3, ..., Fn. I designed idiocy function fi. This is a function which maps features in the range between 0 and 100. You say that we need to model the distributions F_x. How I could do it? Do I need to steal this knowledge from somewhere?

  • @haal4056
    @haal4056 3 месяца назад

    Thank you so much!

  • @akilsaherwala9734
    @akilsaherwala9734 3 месяца назад

    Excellent explanation and presentation

  • @baliamine8790
    @baliamine8790 3 месяца назад

    Best content from best teacher...please continue to share the very interesting contents...following from Algeria :)

  • @nounuame7405
    @nounuame7405 3 месяца назад

    great lecture. is it possible to adjust the density values based on cluster density?. is there any algorithm to achieve this?. thanks

  • @pierriva9196
    @pierriva9196 3 месяца назад

    Super!

  • @RehnumaMaisha
    @RehnumaMaisha 4 месяца назад

    Hi, do you have any Excel file that shows the two-dimensional variogram? Like parallel and perpendicular transects?

  • @JishanAhmed-dr8wh
    @JishanAhmed-dr8wh 4 месяца назад

    Excellent video Professor. May I get access to your PPT slides. Thank you so much for making such amazing lectures open source and accessible.

  • @augustojlle
    @augustojlle 4 месяца назад

    Thanks a lot ! Very clear explanation

  • @__dekana__
    @__dekana__ 4 месяца назад

    You're awesome! Thanks so much for this.

  • @analuisabarbosa6509
    @analuisabarbosa6509 5 месяцев назад

    Thanks great explanation! GeostatsGuy can I ask you what if I have to sample categorical classes. For example, prediction model of land use changes. I would add non-changes but where if i have clustered changes (i.e. changes that occur in one specific region). Thanks!

  • @leandronascimento7046
    @leandronascimento7046 5 месяцев назад

    Thank you Very much!!!

  • @leonidasvonopartis7096
    @leonidasvonopartis7096 5 месяцев назад

    Hi professor, thank you for all your lectures - they are a great resource for fundementals. I wanted to ask, @ 35:24 you speak about creating a 2D ndarrays using the meshgrid function. I wanted to ask why the "-1*" is needed in the arguments for the "yy" array?

  • @shoaibkahut
    @shoaibkahut 5 месяцев назад

    Greetings from #China professor. I am honoured to be your virtual student and always feel pleasure in learning from your videos. Keep inspiring!

  • @muratkaradag3703
    @muratkaradag3703 5 месяцев назад

    Thank you Michael for this awesome video!

  • @guoyu5944
    @guoyu5944 5 месяцев назад

    Is "stationarity" in this lecture similar to "homogeneity"?

  • @pedronader5072
    @pedronader5072 6 месяцев назад

    The way you explain is fantastic. Thank you for making it available for the public!

  • @hadidy13
    @hadidy13 6 месяцев назад

    Thanks Proffesor for helping us and sharing your knowledge, that was really helpful.

  • @abdesselemdehdouh-ch3hv
    @abdesselemdehdouh-ch3hv 7 месяцев назад

    Thanks Pr. Pyrcz

  • @arthur7441
    @arthur7441 7 месяцев назад

    "PromoSM"

  • @user-xc9mo9qh4q
    @user-xc9mo9qh4q 7 месяцев назад

    Happy New Yr, waiting for DS & ML project end-end. kindly make it

  • @LTLn247
    @LTLn247 7 месяцев назад

    This is absolutely amazing. I took Bayesian stats for my MS in Data Science (Analytics) from Georgia Institute of Technology, a top three engineering school, and yet, even as a top tier engineering school, neither the professor nor the TAs bothered to explain these this well. I will be rewatching this several more times. Thank you for the work you put in to create all of this and talk us through it.

  • @vitorribeirosa
    @vitorribeirosa 7 месяцев назад

    Thank you very much for sharing this outstanding content.

  • @user-xc9mo9qh4q
    @user-xc9mo9qh4q 7 месяцев назад

    😍 thx for new topic

  • @_ali_eb2087
    @_ali_eb2087 7 месяцев назад

    thank you very much. I enjoyed your interesting presentation.

  • @neerajvijay5064
    @neerajvijay5064 7 месяцев назад

    Nice explanation

  • @khaledsaleh2605
    @khaledsaleh2605 7 месяцев назад

    Thanks for the very nice demonstration 👍

  • @kolapopoola3114
    @kolapopoola3114 7 месяцев назад

    Thanks as always Mike. I love this short demo series. They are great teasers for deciding what I would like to dig deeper into with your other lectures

  • @bmacmill
    @bmacmill 8 месяцев назад

    When learning about a complex topic, there is a teaching moment when the diverse components make sense together. This video brought disparate parts of my knowledge and experience together brilliantly. I am a software developer who is making the transition from managing financial transactions to analyzing features that explain migration. This video helps me so much. Thank you!!!!

  • @user-xc9mo9qh4q
    @user-xc9mo9qh4q 8 месяцев назад

    Wooow, thx for video

  • @AbhishekSinghSambyal
    @AbhishekSinghSambyal 8 месяцев назад

    Amazing.

  • @ianrickey208
    @ianrickey208 8 месяцев назад

    Awesome! I am loving this series! Thank you!!!

  • @twistedpancake7214
    @twistedpancake7214 8 месяцев назад

    Great stuff, keep it up boss

    • @GeostatsGuyLectures
      @GeostatsGuyLectures 8 месяцев назад

      Thank you! I've got about 44 more to go! :) I hope these are helpful.

  • @hamzacheniti6943
    @hamzacheniti6943 8 месяцев назад

    It's a pleasure to see you again

    • @GeostatsGuyLectures
      @GeostatsGuyLectures 8 месяцев назад

      Thank you! It has been a while! Super busy and excited to keep building more content on RUclips.

  • @aozyhuang5847
    @aozyhuang5847 8 месяцев назад

    It's a clear explanation and very helpful. Much appreciated.

  • @oscarsanroman9369
    @oscarsanroman9369 8 месяцев назад

    Thank you for this, Professor Michael.

  • @jimshtepa5423
    @jimshtepa5423 8 месяцев назад

    is there any section in the courses where you show certain concepts by coding?

  • @holyscam9131
    @holyscam9131 9 месяцев назад

    What can be the physical interpretation of negative correlation? How is it possible that places dislike each other?, Michał Michalak

  • @user-so7uy3cc9c
    @user-so7uy3cc9c 9 месяцев назад

    Great explanation! Thank you!

  • @isaacbarbozavilchez6773
    @isaacbarbozavilchez6773 11 месяцев назад

    So far, very detailed information and abundant of clear examples to meak easier the processing of Geostats learning

  • @EshwarNorthEast
    @EshwarNorthEast 11 месяцев назад

    Why is the case where no one does nothing including player1’s value?