Kaggle Notebook (Housing): www.kaggle.com/code/kenjee/housing-prices-example-with-video-walkthrough Check out the video description for additional resources!
Can you make a whole playlist where you go through different projects because you have a very unique way of teaching and I think a lot of people would benefit from that
You are amazing - this helped me so much - I am on the beginning of my journey and trying to find videos like this where people walk through what they've done. Yours is the best I've come across so far! TY!
Thank you Ken!!! I had no idea on how to do a kaggle challenge or what was expected, but you went through the whole process and explained what each part was!!! Now I have no excuses for a boring kaggle profile
Thanks Ken for the tutorials. I'm not really a fan of your videos because they're not technical enough but I really enjoyed this and learnt a couple of things. Wish you could make more of these
Hi Ken! thanks for making this great tutorial. Can you do tutorial on fine tuning the NLP pretrained model? there are few videos out there but I think you are more advanced on communicating the technical things so it's make us easier to understand. Thanks!
Being on a hill also means less risk of water damage given any runoff will flow downhill. I'm assuming a depression is opposite and runoff will flow and pool towards the hoke
I am a material scientists who works with large data sets and I want to pivot into data science because I've grown to love how data is manipulated and analyzed outside of just scientific applications. academia has been exhausting and I want to refresh things in a new field. Do you by chance do any personal life coaching?? regardless, thank you for your videos, they are both motivational and instructional!!
I don't don any life coaching, but I do try to respond to all comments. If you have any questions, I'm happy to answer them here. You may also find some case studies on my podcast Ken's Nearest Neighbors!
@@KenJee_ds Thanks for your response!! My difficulty lies in finding the best and most efficient pathway to take the knowledge I have (I code in python, I know some advanced excel like macros and VBA basics, I am a theoretician so math is my wheelhouse, I also am familiar with Linux being a Mac person, and I've begun using AI/ChatGPT to help me when coding) and learn what I need to know to apply for a position. I have access to LinkedIn learning and I just found Kaggle through your channel. I am happy to put in the work, I just don't want to waste any time. I really enjoy python coding and SQL is very interesting (I have a small amount of time working with SQL). My goal in pivoting to data science is to find a position either working with a team that manages data for a tech company, or freelance work. My thought is to work through all the Kaggle tutorials, then through the Python + SQL course on LinkedIn Learning, and then actively learn through developing my own projects. I find the hardest information to find when searching data science jobs is how many and at what level do they want your previous projects and where is the best place to look for entry/mid level positions where I can learn on the job as well. Thanks again for your awesome channel and your correspondence with your audience!!
@@eric_welch This seems like a good approach to me! I generally recommend trying to create products or things people will use as much as possible. Dashboards, etc. are very useful in showcasing your skills to prospective employers.
I've been trying to become a data analyst for 2 years, no luck. But data scientists roles are looking more attractive now though, they seem more programming focused and pay a lot more. As far as I can see from the table of contents, the model part is when it turns into data scientist role? I think a Data Analyst would stop st the EDA and then create visuals. Still tryung to figure out the difference between the two! Btw are junior data sci roles easier to land that junior data analyst? All the data roles ive seen at entry level want 3 years experience.. Im any case im gonna follow along here as I have experience with pandas and Python, thanks!
I think to make the code less confusing, the y_test could be replaced by y_valid like some notebooks did so the test suffix is reserved for the real test data. Thank you for your wonderful videos and your codes are always so clean and easy to follow! Cheers!
Wonderful content as always. But you could literally reset the default theme to 'plotly_dark'. This would have been better than repeating most of the layout update.
As a practicing data scientist, how important would you say it is to handle calculations such as integrals by hand? I studied this stuff 10 years ago and have since had my skills atrophy. Though the intuition is still there. Is it worth going through that stuff again or just diving into the deep end?
Sometimes I think i picked the worst year to get into DS , I do love the field, really do, but when the market requires PHD for entry levels.. you know you got yourself into big trouble
Realistically, I think it is a tough time to get into any field. AI will be shaping every single one of them in my opinion. I think data science is as promising as others (not sure if that helps)
@@KenJee_ds hey I also wanted to know your opinion on being great in feature engineering. Whenever I do these projects I feel that I need to know more about feature engineering. I also want to improve in feature engineering incrementalally being more creative.
@@shreyashagrawal9650 I think this is a great way to really differentiate yourself! I think understanding the subject area is really important and if you can show you can do that, it can be very valuable
Well, it seems like your statement is more of a humorous exaggeration than an accurate reflection of reality. Data science is far from dead; in fact, it's more alive and in-demand than ever before.
I don't know if it is dead, but it is definitely changing. One of the reasons I'm pushing using AI tools like this in practice is that I believe they will be a massive part of any career going forward
Kaggle Notebook (Housing): www.kaggle.com/code/kenjee/housing-prices-example-with-video-walkthrough
Check out the video description for additional resources!
Can you make a whole playlist where you go through different projects because you have a very unique way of teaching and I think a lot of people would benefit from that
I actually have one! th-cam.com/play/PL2zq7klxX5ATfW-VhOWiLwoSpHhQfL6AG.html
Half way through and just wanted to say this is very valuble content! Love the walkthrough type if content!
You are amazing - this helped me so much - I am on the beginning of my journey and trying to find videos like this where people walk through what they've done. Yours is the best I've come across so far! TY!
Makes me really happy to hear you found this valuable!
Thank you Ken!!! I had no idea on how to do a kaggle challenge or what was expected, but you went through the whole process and explained what each part was!!! Now I have no excuses for a boring kaggle profile
💪
Thank you for explaining this so well! As a beginner this gave me invaluable insight on how to approach a problem on Kaggle.
Thanks for watching!!
Really AMAZING video! Helps me on my grad journey breaking into data jobs
Glad you found it helpful! Thanks for watching!
Thanks Ken for the tutorials. I'm not really a fan of your videos because they're not technical enough but I really enjoyed this and learnt a couple of things. Wish you could make more of these
Trying to do more of these in the next few months!
Amazing Work Ken. Thank you for explaining so thoroughly :)
Thanks for watching!
This project is amazing! Can you make more videos like that please?
Planning to do more in the next few months!
This has been very informative to see the process and how you included AI in it.
Thanks for watching! Glad to hear it was helpful!
Hi Ken! thanks for making this great tutorial. Can you do tutorial on fine tuning the NLP pretrained model? there are few videos out there but I think you are more advanced on communicating the technical things so it's make us easier to understand. Thanks!
Being on a hill also means less risk of water damage given any runoff will flow downhill. I'm assuming a depression is opposite and runoff will flow and pool towards the hoke
I am a material scientists who works with large data sets and I want to pivot into data science because I've grown to love how data is manipulated and analyzed outside of just scientific applications. academia has been exhausting and I want to refresh things in a new field. Do you by chance do any personal life coaching?? regardless, thank you for your videos, they are both motivational and instructional!!
I don't don any life coaching, but I do try to respond to all comments. If you have any questions, I'm happy to answer them here. You may also find some case studies on my podcast Ken's Nearest Neighbors!
@@KenJee_ds Thanks for your response!! My difficulty lies in finding the best and most efficient pathway to take the knowledge I have (I code in python, I know some advanced excel like macros and VBA basics, I am a theoretician so math is my wheelhouse, I also am familiar with Linux being a Mac person, and I've begun using AI/ChatGPT to help me when coding) and learn what I need to know to apply for a position. I have access to LinkedIn learning and I just found Kaggle through your channel. I am happy to put in the work, I just don't want to waste any time. I really enjoy python coding and SQL is very interesting (I have a small amount of time working with SQL). My goal in pivoting to data science is to find a position either working with a team that manages data for a tech company, or freelance work. My thought is to work through all the Kaggle tutorials, then through the Python + SQL course on LinkedIn Learning, and then actively learn through developing my own projects. I find the hardest information to find when searching data science jobs is how many and at what level do they want your previous projects and where is the best place to look for entry/mid level positions where I can learn on the job as well. Thanks again for your awesome channel and your correspondence with your audience!!
@@eric_welch This seems like a good approach to me! I generally recommend trying to create products or things people will use as much as possible. Dashboards, etc. are very useful in showcasing your skills to prospective employers.
@@KenJee_ds thank you for this information!! i really appreicate your engagement
Strong suggest Andrew Ng's data science course and also get good at SQL as you transition to data science
Great Timing!!Thanks.. following to u with closely
Thanks for watching!
Immedietly i saw this video i also started creating the same project 🤣 thanks !!!!
Amazing! Let me know what you think!
I've been trying to become a data analyst for 2 years, no luck. But data scientists roles are looking more attractive now though, they seem more programming focused and pay a lot more.
As far as I can see from the table of contents, the model part is when it turns into data scientist role? I think a Data Analyst would stop st the EDA and then create visuals. Still tryung to figure out the difference between the two!
Btw are junior data sci roles easier to land that junior data analyst? All the data roles ive seen at entry level want 3 years experience..
Im any case im gonna follow along here as I have experience with pandas and Python, thanks!
I think to make the code less confusing, the y_test could be replaced by y_valid like some notebooks did so the test suffix is reserved for the real test data.
Thank you for your wonderful videos and your codes are always so clean and easy to follow! Cheers!
Good point!
Wonderful content as always.
But you could literally reset the default theme to 'plotly_dark'. This would have been better than repeating most of the layout update.
Good point!
My nga, ure the best!!!
As a practicing data scientist, how important would you say it is to handle calculations such as integrals by hand? I studied this stuff 10 years ago and have since had my skills atrophy. Though the intuition is still there. Is it worth going through that stuff again or just diving into the deep end?
I haven't done an integral once since I started working professionally haha
Hi Ken! Have you had to utilize PCA before?
Not frequently in my day to day work
Hey sir, I would wanna know about this, would you recommend using powerbi for EDA process before model building than pandas?
I generally prefer to do the EDA in python if I can. It really depends on the jobs and skills you're trying to develop though!
can you make a playlist for upcoming projects
I have one already I believe :)
Sometimes I think i picked the worst year to get into DS , I do love the field, really do, but when the market requires PHD for entry levels.. you know you got yourself into big trouble
Realistically, I think it is a tough time to get into any field. AI will be shaping every single one of them in my opinion. I think data science is as promising as others (not sure if that helps)
What was the use of Data Exploration? I feel it played no part whatsoever in the final results of the project.
Where have you used chatgpt?
I used it in bits and pieces in each part of the analysis. I generally say where I do at each step
@@KenJee_ds hey I also wanted to know your opinion on being great in feature engineering. Whenever I do these projects I feel that I need to know more about feature engineering. I also want to improve in feature engineering incrementalally being more creative.
@@shreyashagrawal9650 I think this is a great way to really differentiate yourself! I think understanding the subject area is really important and if you can show you can do that, it can be very valuable
Thanks for the video, Ken. But with all due respect, it's less of a data science tutorial and more of a ChatGPT demo.
haha I think you might be right
Data science is dead lol
The man put a lot of effort on making this video. If you dont have good things to say, remain silent.
Well, it seems like your statement is more of a humorous exaggeration than an accurate reflection of reality. Data science is far from dead; in fact, it's more alive and in-demand than ever before.
I don't know if it is dead, but it is definitely changing. One of the reasons I'm pushing using AI tools like this in practice is that I believe they will be a massive part of any career going forward
No wonder the recent focus on ChatGPT. Thanks for this
I use chat gpt for all my projects. Such a Great tool