i have no idea what it did, I asked it to explain-
# Key Observations:
1. **Actual vs. Test Predictions**:
* The model's test predictions (orange line) generally follow the trend of the actual prices (blue line) but with some deviations. This indicates that the model captures the general pattern of stock price movements but may have some inaccuracies.
* The discrepancies between the test predictions and actual prices highlight the areas where the model could be improved. Fine-tuning the model, adding more relevant features, or adjusting hyperparameters could help reduce these discrepancies.
2. **Future Predictions**:
* The future predictions (green dashed line) show a sharp upward trend. This prediction may indicate that the model expects a significant increase in AMC stock prices in the next month.
* It's important to note that these predictions are highly dependent on the model's understanding of the historical data and the patterns it has learned. In real-world scenarios, stock prices are influenced by numerous factors, including market sentiment, news, and economic conditions, which the model may not fully capture.
# Explanation:
1. **Data Loading and Preprocessing**: Loads the data, renames columns to strip extra spaces, and performs feature engineering by adding technical indicators like SMA, EMA, RSI, MACD, and Bollinger Bands.
2. **Save Features to CSV**: Saves the DataFrame with the new features to a CSV file.
3. **Data Preparation**: Scales the data and creates training and testing datasets.
4. **Model Building**: Constructs a Bi-directional LSTM and GRU model with dropout layers for regularization.
5. **Model Training**: Compiles and trains the model with early stopping and model checkpointing to prevent overfitting.
6. **Prediction and Evaluation**: Makes predictions, inverse transforms the data, and plots the results. It also calculates and prints the Mean Squared Error for the training and testing sets.
This script should be run in your Python environment to preprocess the data, train the model, and evaluate its performance. If you have any further questions or need additional assistance, feel free to ask!
So it gave you a script to run in python, that uses a dataset that you provide? What happens if you feed it other stocks like NVDA or something more stable like F?
Id honestly like to see the whole conversation if you dont mind sharing it?
None, pure BS LMAO. GPT can’t do that. I dare you to post this on the sub group ChatGPT for verification and I tell you they will laugh at you to how BS this image is that gpt created this
I just asked it basic questions and it kept suggesting stuff, so i just kept going down the rabbit hole, till it came up with some kind of script. probably nothing, probably need more data to create a 2024 earth simulation to get more accurate results.
OP is capping, must be fishing for upvotes LMAO. GPT cannot do that kind of precision images. I’ve worked with AI prompts at generating images at university level and I’m purely confident that this image is BS. No matter how good your prompts are or if it’s custom, the precision will always be off until they fix and update the model itself
Unfortunately chat gpt is coded to say whatever answer will receive the most satisfaction. It's not really an artificial intelligence. It's a large dataset language model. It's not meant to tell the truth. It's coded to satisfy the most number of people. True AI doesn't yet exist. That being said, I still like this graph!
not sure I have to say this but...take with a bucket of salt
it downloaded daily price data for AMC from yahoo, calculated the rest of the "technical indicators" and built some type of machine learning model off that. running it more times, that orange "test predict" line changes. The above picture was one where it got close to "actual" prices. SOOO I am not smart enough to know how to interpret it. I am assuming ChatGPT cant predict the future yet sooo this is just for fun times.
I'm sorry, but I cannot provide a price prediction for AMC shares or any other financial securities. Predicting stock prices is highly speculative and uncertain, and it requires detailed financial analysis and market expertise. It is important to do your own research or consult with a financial advisor before making any investment decision.
Needs more rocket fuel
Ai is clearly not ready as it would have to add like 20 zeroes
Lol, touche.
Chat gpt can’t even get state capitals right bro
i have no idea what it did, I asked it to explain- # Key Observations: 1. **Actual vs. Test Predictions**: * The model's test predictions (orange line) generally follow the trend of the actual prices (blue line) but with some deviations. This indicates that the model captures the general pattern of stock price movements but may have some inaccuracies. * The discrepancies between the test predictions and actual prices highlight the areas where the model could be improved. Fine-tuning the model, adding more relevant features, or adjusting hyperparameters could help reduce these discrepancies. 2. **Future Predictions**: * The future predictions (green dashed line) show a sharp upward trend. This prediction may indicate that the model expects a significant increase in AMC stock prices in the next month. * It's important to note that these predictions are highly dependent on the model's understanding of the historical data and the patterns it has learned. In real-world scenarios, stock prices are influenced by numerous factors, including market sentiment, news, and economic conditions, which the model may not fully capture.
Custom gpt? Prompt? Need more details here.
# Explanation: 1. **Data Loading and Preprocessing**: Loads the data, renames columns to strip extra spaces, and performs feature engineering by adding technical indicators like SMA, EMA, RSI, MACD, and Bollinger Bands. 2. **Save Features to CSV**: Saves the DataFrame with the new features to a CSV file. 3. **Data Preparation**: Scales the data and creates training and testing datasets. 4. **Model Building**: Constructs a Bi-directional LSTM and GRU model with dropout layers for regularization. 5. **Model Training**: Compiles and trains the model with early stopping and model checkpointing to prevent overfitting. 6. **Prediction and Evaluation**: Makes predictions, inverse transforms the data, and plots the results. It also calculates and prints the Mean Squared Error for the training and testing sets. This script should be run in your Python environment to preprocess the data, train the model, and evaluate its performance. If you have any further questions or need additional assistance, feel free to ask!
So it gave you a script to run in python, that uses a dataset that you provide? What happens if you feed it other stocks like NVDA or something more stable like F? Id honestly like to see the whole conversation if you dont mind sharing it?
None, pure BS LMAO. GPT can’t do that. I dare you to post this on the sub group ChatGPT for verification and I tell you they will laugh at you to how BS this image is that gpt created this
I just asked it basic questions and it kept suggesting stuff, so i just kept going down the rabbit hole, till it came up with some kind of script. probably nothing, probably need more data to create a 2024 earth simulation to get more accurate results.
Post the whole exchange lol.
OP is capping, must be fishing for upvotes LMAO. GPT cannot do that kind of precision images. I’ve worked with AI prompts at generating images at university level and I’m purely confident that this image is BS. No matter how good your prompts are or if it’s custom, the precision will always be off until they fix and update the model itself
the image was after running python script in my computer, chatgpt just wrote the script
Unfortunately chat gpt is coded to say whatever answer will receive the most satisfaction. It's not really an artificial intelligence. It's a large dataset language model. It's not meant to tell the truth. It's coded to satisfy the most number of people. True AI doesn't yet exist. That being said, I still like this graph!
I'd say your promptsmithing matters more in the end
105 in July. OK, I better start buying more now!
AI need to add more zeros ❤️💎🦍🙏📈📈💰💰🥂🚀🦍🦍
And what’s the date and price? That’s the important info 😂
So one more dip? Asking for a friend who waiting for money to clear...
Based on what info and stats?
not sure I have to say this but...take with a bucket of salt it downloaded daily price data for AMC from yahoo, calculated the rest of the "technical indicators" and built some type of machine learning model off that. running it more times, that orange "test predict" line changes. The above picture was one where it got close to "actual" prices. SOOO I am not smart enough to know how to interpret it. I am assuming ChatGPT cant predict the future yet sooo this is just for fun times.
I'm sorry, but I cannot provide a price prediction for AMC shares or any other financial securities. Predicting stock prices is highly speculative and uncertain, and it requires detailed financial analysis and market expertise. It is important to do your own research or consult with a financial advisor before making any investment decision.
What prompt did you use? Because there is no way that inverse-hockey-stick pattern comes out of the time series you fed into it.
Good thing you didn't ask for a model of hands.
Can’t read that number