An Intro to Markov chains with Python!

[@spiderjerusalem]

This is one of the BEST Python tutorials I have ever seen, not just among Markov Chain tutorials, but among all tutorials. Great work!

[@dzuynguyen8256]

Really pulled me out of a dark place man. Thank you.

[@TheDunningKrugerEffectisReal]

Good stuff, I'm going to save it to watch it again later.

[@uniqueninja6197]

Thanks Adrian for this tutorial on HMM. Thanks for being so simple and practical on the concept.

[@Raggaliamous]

Completely fantastic. Plus, I appreciate the ending references. Interested in making a basic weather simulator, I'm now searching a simple way of harvesting open weather data, to formulate the probabilities.

[@Raggaliamous]

I wish I new. I just improvised instead...@theman1860

[@HonestADVexplorer]

Thank you very much! Clean Python code and clear explanations!

[@ddiq47]

Thanks for including the reference for that book, definitely going to check that out!

[@reanwithkimleng]

❤❤❤❤ merci monsieur

[@gmonkman]

Great explanation. I see the mathematical notation descriptors and just switch off, but this practical example is great. Respect for the credits as well.

[@breadandcheese1880]

Hands down the best example; Professors in universities please take note.

[@entahgatau]

why after several iterations on n-step transitions, the rows become the columns and vice versa?

[@PatrickNieto]

Is there a way to implement this if there were conditions on the transitions. I guess if it wasn't memorylessness. For example, what if I could only go to Seoul if I hadn't gone to Cairo or Paris the last 7 states?

[@gmonkman]

Dunno if there is an elegant way, but you'd detect in the loop on if you are in Cairo or Paris and adjust the step transition matrix

[@carrotsofallages7369]

Hello, thanks for the video :). I wanted to ask what to do if you get a KeyError. Or how that error occurs in the first place

[@RA777FBI]

How did you show the plot of the markov chains?

[@AdrianDolinay]

I used Photoshop for the chain showing the movement to different cities. It wasn’t a Python package

[@rodrigobotello2093]

Hello! when I use the code of the matrixpower, it says that matrix power is not defined, can you help me with it?

[@AdrianDolinay]

matrix_power is a user defined function. If you run the code snippet below it will create the function in your environment. Make sure you also have NumPy imported to run the function. Let me know if you have any additional questions and hope this helps! def matrix_power(matrix, power): if power == 0: return np.identity(len(matrix)) elif power == 1: return matrix else: return np.dot(matrix, matrix_power(matrix, power-1))

[@shhreyaanand7444]

Hi why isn't the blue graph showing?

[@AdrianDolinay]

Which time stamp are you referring to?

[@rajeshmanjrekar3614]

while len(travel_sim) < 25: city=np.random.choice(mc.iloc[mc.index.get_loc(city)].index,p=mc.iloc[mc.index.get_loc(city)]) travel_sim.append(city) when i run this code it says p has to be one-dimensional as ERROR

[@AdrianDolinay]

Not sure about the error without seeing the rest of your notebook. If you download the notebook from GitHub and compare it to your own script that should reveal why you are getting the error. Please let me know if you continue to have issues.

[@AdrianDolinay]

Not sure about the error without seeing the rest of your notebook. If you download the notebook from GitHub and compare it to your own script that should reveal why you are getting the error. Please let me know if you continue to have issues.