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If there are a multiple input values how that have to be inserted in the cvs data ?

stemmer2 doesn't stem 'having' because it's a stopword in NLTK stopwords -- is that correct?

Hi everyone! I have a noobie question. AutoTrain advanced CLI: error: unrecognized arguments: --output model/ How to fix this error and specify the output model?

Hyy sir I'm want to know whole about ML Olympiad

results are not same. Am I miss iterpretting?

How do we forecast when changepoint exist in hierarchical data?

such a beautiful journey sir you are our inspiration ❤

Can we try doing this with a phone?

## [00:00] Introduction - This video provides guidance on how to launch a career in data science. - The speaker will answer frequently asked questions about becoming a data scientist. ## [00:56] Learning Path for Data Science - The most common question is regarding the learning path for aspiring data scientists. - This section will cover recommended courses, educational paths (e.g., MBA, PhD), and statistics knowledge required. - It will also address how to find an internship in data science. ## [02:44] Online Courses for Data Science - Supplement Andrew Ng's courses with additional resources like courses from Kaggle Learn. - Develop practical skills by working on exercises from the courses. - Avoid copying solutions and focus on understanding the concepts through practice. ## [05:22] Paid Courses and Certifications for Data Science * Be cautious of expensive data science courses and certifications. * Seek reviews from previous students before enrolling in paid courses. * Focus on building your own projects to showcase your knowledge over certifications. ## [07:24] Formal Education for Data Science * University courses in machine learning, data science, and data mining are valuable for beginners. * A master's degree can be sufficient for industry jobs, while research may require a PhD. * PhD graduates may need to improve coding skills to transition to industry jobs. ## [10:16] Learning Machine Learning Algorithms * A practical approach to learning algorithms involves using cheat sheets as a starting point. * Complement this approach with research and hands-on implementation using libraries like scikit-learn. * Google searches and reading documentations can provide deeper understanding of the algorithms. ## [12:45] Learning Data Science by Doing * Applying learned concepts to real-world projects is crucial for practical machine learning skills. * Public datasets and machine learning competitions are great resources to find project ideas. * Start with simple projects and gradually progress to more complex ones as you learn. ## [15:16] Asking Questions Effectively in Data Science * Before asking questions online, try your best to solve the problem yourself and isolate the specific part you don't understand. * When asking questions on forums, provide context about your work and what you've already tried. * Phrase your questions clearly and specifically to get helpful answers. ## [18:57] Building a Data Science Portfolio with Projects * Working on real-world data science projects is crucial for building a strong portfolio. * Aim to complete multiple projects to showcase your skills and experience. * Consider open-sourcing your code and writing blog articles about your projects to gain recognition.

Thank you SOOO much for making those videos to teach us!!!It's genuinely helpful for me to learn Python. There'is not enough resources for me as a high school student to learn and understand Python, but through your free vedios online I think I'm doing a good job studying it! Lots of thanks

Are you planning on making a chatbot for Llama 3?

can i train llama3 also with these steps?

how do you get access to the llama model?

Once the image is built, it won't go away, isn't it? And how did you make your settings? Thank you great video

is there hyperparameter for cnn

Hello sir, can you reopen the data? This contest is no longer available. Thank you.

indian...

hi, I just found out about your AAAML book, but cant find the code repo of it, could you please share it?

which machine is recommended for fine-tuning LLAMA? windows?

Incredibly helpful video, I appreciate that you took the time to create this! Great stuff

When will I be able to see the model that I have trained? Once all the training is complete?

Where's your next video! Your channel always inspires me!!!! Cant wait to watch your new video

I have llm downloaded can I fine tune it with downloading from huggingface.

This keeps giving an error message . When this happened to you, you said That you forgot to export the environment variable WHICH IS????

I know it could be too much but could you also make a video of how to prepare the data? I have like 'question' and 'answer' but I am strugging to make it to a trainable data set into that kind of csv so I could use it!

You missed to add relu before double conv in expansive block. But great explanation, thankyou!

simply best

Thank you for this excellent presentation/tutorial! Are there other optimization methods that can be used apart from the ones you have covered in this video? Do you also work on metaheuristic optimization methods? If yes, I would like you to drop a video on it.

Keeping it this simple is something very few people are able to do. Very well explained. This can be understood by even a beginner. Atleast the execution if not the intuition behind it. Kudos

sad you don't provide the full code c/C...

HI Abhishek. Thanks for posting some interesting videos. I tried doing text to speech using Bark on V100 GPU on Bark. It is taking too long. I need latency of less than a second. Can you recommend how I could achieve that.

Hi Sir, humble request, can you please share your journey of being kaggle grandmaster and guide the juniors out here. If you already have posted somewhere, would love to have link to it. 😁

thank,from china

thanks bro ❤

please mention the computing power required

tnx

can anyone tell me whats prerequisite ??

how to get this kind of detailed terminal?

Clean boy !

Can you make a video for fine tuning in silicon macs ?

is it multilingual?

How do you convert it to work with Ollama? I setup the model file and it doesnt seem to know anything from my training.

Amazing! Thank you.

TODAY 2024 MARCH 6TH , MY KAGGLE JOURNEY STARTED

Great vid

Sir i need a video on how to train the code with dataset and if we give an image it should return the segmented one, how to do so with this UNet? Please do a video on it as soon as possible. Or if there is anyother video and if anyone knows which one is better kindly reply for this message with the link of the video.

what if we've toooo many targets? will it be applicable?

Colab has banned it.

2:55 Tabnet Paper introduction 4:20 Main ideas from Tabnet 7:21 Architecture 8:55 feature transformer block 10:51 attentive transformer block 14:25 individual explainability intro 15:10 self supervised learning ( pretrainning ) 17:10 pytorch implementation intro ( 19:18 fastai wrapper avialable ) 20:59 demo from a notebook 29:34 Kaggle competition notebooks using Tabnet Pytorch 29:55 Code base architecture 32:18 tricky implementation tips! 34:36 future work 40:52 QA session 41:09 explainability 42:30 computing resource 43:50 tabnet parameters explain 47:55 feature selection ( from sparse mask)

hi. please help me. how to create custom model from many pdfs in Persian language? tank you.