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@srishtichy6 ай бұрын
Very helpful video on the use of Gemini and Open AI APIs for sentiment analysis. Thanks for uploading. Can you also share the steps to generate the Google API key?
@Analyticsvidhya6 ай бұрын
Check out this tutorial for Gemini API Key: kzbin.info/www/bejne/pnukq5pueLSFj6s
@krishtyagi2238 ай бұрын
1 no video
@aniketchejara25258 ай бұрын
Become Always nice video
@sravannemiwal72558 ай бұрын
🔥🔥🔥🔥🔥🔥
@ared59 ай бұрын
I have a dataset with around 4M reviews, I've tried doing sentiment analysis on it using the Transformers pipeline with distilbert but it was way too slow. can you tell me how many batches should I make If I have to use chatgpt API and what would be a cost and time-efficient solution?
@Analyticsvidhya8 ай бұрын
Dear learner, before jumping onto ChatGPT API, we would recommend you to try out programmatic labelling for your specific use case of Sentiment Label Generation - using the free Snorkel framework. Otherwise, to answer your question, batch-size will depend on the context window of the Model you are using. Here's a cost sheet you may refer to for your evaluation. It has details on context window as well: docs.google.com/spreadsheets/d/1A57gqIpTDC6qEgZIal3tsTvFzo2oxg-5M0ky_drAdM8/edit?usp=sharing
@totorototoro-o7o7 ай бұрын
love you my brother
@anurajCanada24 күн бұрын
i added my open Ai api key to the key and it says i have exceeded the limit even i tried different api key from different google registered account
@lawrencealleyne14279 ай бұрын
is it possible to adjust the prompt so that it can analyze the text and not just identify positive and negative reviews, but also identify recurring issues and summarize what it reads?
@Analyticsvidhya9 ай бұрын
Absolutely, yes. You may modify your prompt- asking model to capture issues mentioned in reviews and share that as a separate parameter in the output json. For example, apart from the two parameters we have: Review and Sentiment Label, you may add another one called- Issue.
@sports_channel18 ай бұрын
I am working on a project that requires to perform the sentiment analysis on comments of social media posts which approach is better LLM or NLP? Or got any other suggestions to make it better?
@Analyticsvidhya8 ай бұрын
Ideally try both. Specific to LLMs, you may use Gemini API that comes free for development purpose.
@aadilgani94027 ай бұрын
I want to use the same approach for aspect-based sentiment analysis, the dataset has sentence, sentiment, target and aspect. the model should predict sentiment, target and aspect i.e. multi-head prediction is it possible with this approach.
@Analyticsvidhya7 ай бұрын
Great use case. You may try out the discussed prompt engineering approaches for this use case. Depending on the size of your labelled dataset, you may also try out fine-tuning a smaller Language Model, like quantized Llama 3.
@victoradejuwon94143 ай бұрын
i am writing a project which inolves sentiment analysis of a particular topic on twitter. i have already extracted the data, how will you suggest i label it
@xIRedIx3 ай бұрын
How did you extract data from Twitter? Can you kindly share? A program or a paid service?
@adanulabidin5 ай бұрын
ChatGPT API not generating response and displaying RateLimitError. What to do?
@Analyticsvidhya4 ай бұрын
Try reducing batch size and adding increased delay using Python time sleep module.
@halfbloodyash85922 ай бұрын
how can I save this model ??
@advait52118 ай бұрын
i have a project which takes tweets and analyses trends in a given area : traffic trends , political trends , restraunts , etc , instead of NLP can i use gemini or open ai?
@Analyticsvidhya8 ай бұрын
Gemini API comes for free for development purpose. OpenAI also give $5 worth of free credits.
@sairamteja67857 ай бұрын
where are you fine tunning the gemini model???
@Analyticsvidhya7 ай бұрын
In the Few Shot prompting part - where we are giving examplers.
@chrisdsilva71149 ай бұрын
What if you are working with a dataset that has no true values?
@goutham64059 ай бұрын
Even you don't any able Google model will able to predict the position and negative sentence. Which is not clear . Better to use labelled data
@Analyticsvidhya9 ай бұрын
You may use some programmatic labelling technique, like snorkel. Else generate labels, and then manually validate a sample (which is statistically significant) for your error tolerance.
@ashwinialli92848 ай бұрын
i am working on project about share market trend for last yr using Gemini API can i use this project by replacing dataset with share market dataset? provide some guidelines to this project.
@Analyticsvidhya7 ай бұрын
Sentiment analysis project (video) focuses on text, not ideal for stock trends. Here's how to adapt for your project: 1. Use share market data APIs (e.g., Alpha Vantage) for historical data (past year). 2. Transform data (e.g., moving averages) for analysis. 3. Optional: Build a model (machine learning) to predict future trends (be cautious!). 4. Use Gemini to analyze data, identify patterns, or visualize trends. Good luck with your project!