Python Code Streamliner
Python coding assistant. Ask Python-related questions and PCS will answer. Request code and PCS will generate it. Provide your code as context and ask PCS to extend, debug, refactor, modify...
- Ratings
- 4(4)
- Conversions
- 500+
- Author
- @talkingtochatbots.com
- Links
- Website https://talkingtochatbots.com
- Linkedinhttps://linkedin.com/in/davidgonzalezromero
- Githubhttps://github.com/reddgr
- Twitterhttps://twitter.com/dgromero
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Features and Functions
- Knowledge file: This GPT Contains knowledge files.
- Dalle: DALL·E Image Generation, which can help you generate amazing images.
- Python: The GPT can write and run Python code, and it can work with file uploads, perform advanced data analysis, and handle image conversions.
- Browser: Enabling Web Browsing, which can access web during your chat conversions.
- File attachments: You can upload files to this GPT.
Conversion Starters
- Add ReduceLROnPlateau and Early Stopping callbacks to this training: hist = model.fit(X_train, y_train, validation_split=0.1, epochs=50, batch_size = 35)
- Write a function that simulates a stochastic oscillator for algorithmic trading
- Define a daily date range spanning 20 years. Then write the Matplotlib code that, given an interest rate r and an initial capital Ci, plots the following two time series Cf_sIR = Ci * (1+ r* (t/365) ) \ Cf_cIR = Ci * (1+r)**t
- date.today() returns 2024-02-20. Write the code that returns a string with '20/2/2024' in this case
- Add ReduceLROnPlateau and Early Stopping callbacks to this training: hist = model.fit(X_train, y_train, validation_split=0.1, epochs=50, batch_size = 35)
- Create a function that calculates a one-hot encoded matrix given an input data frame and a list with the columns we want to one-hot encode. Then create a function that calculates the Euclidean distance between any two items in the original data frame (identified by their index label), based on the one-hot encoded values obtained from the first function
- Given a Pandas dataframe markowitz_rets, with expected daily returns for a given year (index: date, columns: assets), the covariance matrix (mat_cov), and a risk free rate (rfr), write a function (using a library such as scipy) that optimizes the Sharpe ratio of a portfolio, returning weights, expected returns, expected volatility (standard deviation) and Sharpe ratio
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Python Code Streamliner conversion historical statistics
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