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Kody Powell
Приєднався 10 сер 2011
Machine Learning in Python: Plotting the Training History from an ANN Model
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seaborn with a correlation heat map.
To download the Module9Data.csv dataset used throughout this module, click here: kodypowell.che.utah.edu/wp-content/uploads/sites/3/2024/04/Module9Data.csv
For the prior lecture video in this series, click here: ua-cam.com/video/okZgvcW4dVM/v-deo.html
For the next lecture video in this series, click here: ua-cam.com/video/U_3dP7g_HVM/v-deo.html
For a playlist of all lectures for the Smart Systems course, click here: ua-cam.com/play/PLliuty-DnCefs098rXyVkBDAqP-oRElgw.html
To download the Module9Data.csv dataset used throughout this module, click here: kodypowell.che.utah.edu/wp-content/uploads/sites/3/2024/04/Module9Data.csv
For the prior lecture video in this series, click here: ua-cam.com/video/okZgvcW4dVM/v-deo.html
For the next lecture video in this series, click here: ua-cam.com/video/U_3dP7g_HVM/v-deo.html
For a playlist of all lectures for the Smart Systems course, click here: ua-cam.com/play/PLliuty-DnCefs098rXyVkBDAqP-oRElgw.html
Переглядів: 206
Відео
Machine Learning in Python: Making Predictions with an ANN Model
Переглядів 3713 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Evaluating a Multi-Layer Perceptron Model
Переглядів 1303 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Training a Multi-Layer Perceptron
Переглядів 2163 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Training Artificial Neural Networks
Переглядів 1893 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Introduction to Artificial Neural Networks
Переглядів 1483 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Correlation Coefficients and the Seaborn Heat Map
Переглядів 2183 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Machine Learning in Python: Data Analysis with the Seaborn Pairplot Tool
Переглядів 2203 місяці тому
In this module, we cover more advanced machine learning using artificial neural networks (ANNs), specifically the multi-layer perceptron. We show how to pre-process the data including scaling. How to train ANNs and plot the history. Throughout this module, we use tools from the Keras package in Python. We also show how to analyze data using Seaborn pairplots, do correlation analysis using Seabo...
Optimization with Python and SciPy: Convexity and Global vs. Local Optima
Переглядів 1614 місяці тому
In this module, we continue teaching about optimization including nonlinear programming, equality constraints, degrees of freedom, convexity, global vs. local optima, etc. For the previous video lecture in this series click here: ua-cam.com/video/r_x-7X7B_aM/v-deo.html For the next video lecture in this series click here: ua-cam.com/video/OZHoWeoZdQw/v-deo.html For a playlist of all video lectu...
Optimization with Python and SciPy: Equality Constraints
Переглядів 1574 місяці тому
In this module, we continue teaching about optimization including nonlinear programming, equality constraints, degrees of freedom, convexity, global vs. local optima, etc. For the previous video lecture in this series click here: ua-cam.com/video/KeVb5IOzE50/v-deo.html For the next video lecture in this series click here: ua-cam.com/video/Q-n0TbxcyaI/v-deo.html For a playlist of all video lectu...
Optimization with Python and SciPy: Nonlinear Programming (NLP) and Degrees of Freedom (DOFs)
Переглядів 1974 місяці тому
In this module, we continue teaching about optimization including nonlinear programming, equality constraints, degrees of freedom, convexity, global vs. local optima, etc. For the previous video lecture in this series click here: ua-cam.com/video/X0LvnxSqfNk/v-deo.html For the next video lecture in this series click here: ua-cam.com/video/r_x-7X7B_aM/v-deo.html For a playlist of all video lectu...
Optimization with Python and SciPy: Updating a Model for Real-Time Optimization (RTO)
Переглядів 2004 місяці тому
In this module, we introduce the concept of optimization, show how to solve mathematical optimization problems in Python and SciPy, introduce unconstrained optimization, constrained optimization, and real-time optimization including topics such as model parameterization and real-time optimization (RTO). For the previous video lecture in this series click here: ua-cam.com/video/WYT2GQrQpBw/v-deo...
Optimization with Python and SciPy: Real-Time Optimization (RTO)
Переглядів 6294 місяці тому
In this module, we introduce the concept of optimization, show how to solve mathematical optimization problems in Python and SciPy, introduce unconstrained optimization, constrained optimization, and real-time optimization including topics such as model parameterization and real-time optimization (RTO). For the previous video lecture in this series click here: ua-cam.com/video/h31cyV1y2nE/v-deo...
Optimization with Python and SciPy: Multiple Constraints
Переглядів 2804 місяці тому
In this module, we introduce the concept of optimization, show how to solve mathematical optimization problems in Python and SciPy, introduce unconstrained optimization, constrained optimization, and real-time optimization including topics such as model parameterization and real-time optimization (RTO). For the previous video lecture in this series click here: ua-cam.com/video/_aNYFXwzFno/v-deo...
Optimization with Python and SciPy: Constrained Optimization
Переглядів 4274 місяці тому
In this module, we introduce the concept of optimization, show how to solve mathematical optimization problems in Python and SciPy, introduce unconstrained optimization, constrained optimization, and real-time optimization including topics such as model parameterization and real-time optimization (RTO). For the previous video lecture in this series click here: ua-cam.com/video/WYwlyCS8nF8/v-deo...
Optimization with Python and SciPy: Unconstrained Optimization
Переглядів 3414 місяці тому
Optimization with Python and SciPy: Unconstrained Optimization
Optimization with Python and SciPy: Introduction
Переглядів 4544 місяці тому
Optimization with Python and SciPy: Introduction
Machine Learning with Python and SKLearn: Feature Importance and Scaling
Переглядів 2014 місяці тому
Machine Learning with Python and SKLearn: Feature Importance and Scaling
Machine Learning with Python and SKLearn: Elastic Net Regression
Переглядів 1624 місяці тому
Machine Learning with Python and SKLearn: Elastic Net Regression
Machine Learning with Python and SKLearn: Ridge Regression
Переглядів 1954 місяці тому
Machine Learning with Python and SKLearn: Ridge Regression
Machine Learning with Python and SKLearn: The LASSO Algorithm for Regularization
Переглядів 1904 місяці тому
Machine Learning with Python and SKLearn: The LASSO Algorithm for Regularization
Machine Learning with Python and SKLearn: Fitting a Nonlinear Model
Переглядів 3624 місяці тому
Machine Learning with Python and SKLearn: Fitting a Nonlinear Model
Machine Learning with Python and SKLearn: Fitting a Linear Multivariate Model
Переглядів 2194 місяці тому
Machine Learning with Python and SKLearn: Fitting a Linear Multivariate Model
Machine Learning with Python and SKLearn: Introduction
Переглядів 1664 місяці тому
Machine Learning with Python and SKLearn: Introduction
Data Visualization in Power BI: Tutorial Part 4
Переглядів 1275 місяців тому
Data Visualization in Power BI: Tutorial Part 4
Data Visualization in Power BI: Tutorial Part 3
Переглядів 1075 місяців тому
Data Visualization in Power BI: Tutorial Part 3
Data Visualization in Power BI: Tutorial Part 2
Переглядів 945 місяців тому
Data Visualization in Power BI: Tutorial Part 2
Data Visualization in Power BI: Tutorial Part 1
Переглядів 1625 місяців тому
Data Visualization in Power BI: Tutorial Part 1
Retrieving and Plotting Results from the Collimator API in Python
Переглядів 1145 місяців тому
Retrieving and Plotting Results from the Collimator API in Python
An Application Programming Interface (API) for Python and Collimator
Переглядів 1585 місяців тому
An Application Programming Interface (API) for Python and Collimator
Hello. Thank you for your video about heat generation. I have a question. In a steady-state, according to the thermal conductivity, temperature distribution is different in a equilibrium (unlimited time)? I am sure that in a transient state, it will be different, but in a steady-state, I am not sure about the situation by different thermal conductivity.
love it, thank you
Thank you Mr.Powell for this valuable video course.
thanks man
thank you for much
Wish my lectures had any form of love for what they do. Thanks for the great lectures.
Very grateful for this explanation Mr Powell. Couldn't get any more convincing than this. 🙏🏽🙏🏽
That excellent thank you so much 😊
hello, can I get access to the textbook that you are extracting these courses from please?
Helpful and straightforward, thanks!
Thank you very much. It was so , so useful !!!
I got a question that how to calculate the free nusselt number when the plate is inclined? Anyone can help me?
nice
I have more coding experience in Matlab than python. Fouriers law says q=-kAdT/dx. Donald trump set a boundary condition on the southern border! Zero flux boundary condition! Sophisticated code like paul smiths laboratory!
The heat transfer equation is from advanced transport phenomena 2, and were coding in python in reaction engineering. Brandon Tatum messaged me what does chemical engineering have to do with my presidential campaign and honestly i dont know. Brandon, my goal is to get healthy as a chemical engineer. Im learning about chemical engineering while waiting for my presidency to happen.
Thank you . If the pipe is porous , can we consider it as thin pipe ? what you do think about this case of porous pipe ?
Thank you so much for the amazing tutorials. I am designer at Nike and work in innovation. Collimator is a fantastic tool for anyone working in a node based environment. I hope you will add more tutorials if possible. Thank you so much for sharing your knowledge!
what is the numerical value for U when you plugged in everything to solve for Tho
❤
Great explanation
Clear and concise! Numerical examples will help a lot the understanding.
first
Is the numerator of ln term the initial of final temperature difference? The book I am using shows the numerator as the final temperature difference. Either way, thank you for this video!
You are a lifesaver, this video was more helpful than the actual lab instructions/instructor!
I might be wrong but I think you forget to multiply cross sectional area in the conduction term at minute 10:41. Still very helpful thanks
❤
hi can you arrange the playlist videos in order??
can we do process modelling using this pycollimator?
Yes! ua-cam.com/video/DhFTOra3m-E/v-deo.html
It's a lot like Simulink, but uses Python. It's great! ua-cam.com/video/awT4fK9B5_0/v-deo.htmlsi=gLqN0Hpyt_v4ujcf
@@kodymerlin1 thanks !
Why is the surface temp. 288K? It wasn't explained so I'm a bit confused.
Just saved me the trouble of looking for problems then a separate answer key. This review is great THANK YOU!
very useful information, thanks for the content!
Please speak in hindi.
popping up the one direction meme was unexpected and cute, thanks for clear explanation >33
Did you ever post the lecture videos for chapters 12 and 13 on radiation? Thank you for posting these videos! I have learned so much from them!
Interesting. Thanks for introducing this to a wider range of ordinances.
Nice Simulink for Python users!
why does convective resistance of boiling water equal 0 here? If I look it up, it has a value range
Dear Sir, thanks for this valuable method for calculate heat transfer...im preparing my thesis and want to use this method and would you like to share this method's source with me, i will he gratefull... İmmediatly waiting your response dear teacher.. thanks for alot and have a nice day
CAn you make one using fem?
I can't thank you enough sir you've explained this far better than my teacher
perfect lecture thank you from Iran
Thanks for great lecture!!!
You are a hero, sir. Thank you for these videos. I learned enough of heat transfer in the last 24 hours to pass the exam I take in 90 minutes, despite knowing almost nothing before. I am forever indebted to you and your excellent instruction style.
What is Z in this case?
The third dimension, which is not used
simple explanation 💯
great explanation professor. thank you so much for your efforts!
You are a god, a heat transfer god.
I owe you my life rn
Hello! Thanks for the video, where can I download the excel?