Enhancing Python Code Prediction for a Neural Network (machine learning)
Budget: €100 – €150 EUR
I am looking for a skilled freelancer to enhance the Python code prediction for a ANN or Recurrent Neural Network (RNN) in the field of machine learning.
Skills and Experience:
- Strong knowledge and experience in working with ANN/RNNs
- Proficient in Python programming language
- Familiarity with machine learning algorithms and techniques
- Experience in optimizing and improving the performance of neural networks
Project Requirements:
-I wrote Python code in Colab to learn from an Excel dataset. There are 500 rows, each has 4 inputs. Each row has one output. At the moment I can't get it done, that the network learns the 500 inputs with their specific output. So if I use exact the same inputs of one of the 500 datasets, then I get a different output than it is in the learning dataset.
- The goal of this project is to achieve specific performance improvement targets in the Python code prediction.
- you get the latest version of the code and the Excel
- I will need help on further developments on this, so if you do a good job there will be more to do
-From my point of few it's not a difficult task, I'm just a bit more than a beginner
-Yes the dataset considts out of valid data, which should be learnable. I could tell you the rules the network should follow
- It's up to you if you want to improve the code or write it completely new but in the end it should do the same steps like saving the model, print and write the prediction in a cell (like it does at the moment).
If you have the necessary skills and experience in working with ANN/RNNs and improving the performance of neural networks, please apply for this project.
Skills and Experience:
- Strong knowledge and experience in working with ANN/RNNs
- Proficient in Python programming language
- Familiarity with machine learning algorithms and techniques
- Experience in optimizing and improving the performance of neural networks
Project Requirements:
-I wrote Python code in Colab to learn from an Excel dataset. There are 500 rows, each has 4 inputs. Each row has one output. At the moment I can't get it done, that the network learns the 500 inputs with their specific output. So if I use exact the same inputs of one of the 500 datasets, then I get a different output than it is in the learning dataset.
- The goal of this project is to achieve specific performance improvement targets in the Python code prediction.
- you get the latest version of the code and the Excel
- I will need help on further developments on this, so if you do a good job there will be more to do
-From my point of few it's not a difficult task, I'm just a bit more than a beginner
-Yes the dataset considts out of valid data, which should be learnable. I could tell you the rules the network should follow
- It's up to you if you want to improve the code or write it completely new but in the end it should do the same steps like saving the model, print and write the prediction in a cell (like it does at the moment).
If you have the necessary skills and experience in working with ANN/RNNs and improving the performance of neural networks, please apply for this project.