AIBootcamp

Data preparation

Data Encoding (Ordinal): data_preparation_examples - ln[4]
Data Encoding (Cardinal, one hot encoding): data_preparation_examples - ln[6]
Missing data management: data_preparation_examples - ln[14], ln[15]

Sentiment analysis with Recurring Neural Networks, Long Short Term Mem

Sentiment Analysis with LSTM (RNN): Sentiment_RNN.ipynb

Classification Regression KPIs

Classification KPI examples (Notebook): Accuracy_Recall_PValues_R2 - ln[1]
Regression KPI examples (Notebook): Accuracy_Recall_PValues_R2 - ln[10]

Supervised Fine-tuning of Pre-Trained Models

See please fine_tuning_colab_GPT2.ipynb See please training and testing datasets in datasets folder

Local LLM model dry & run

See Ollama.md for details

Local LLM model dry & run advanced with RAG

See RAF_Local.md for details

Cheshire Cat hands-on

See Cat.md for details

RAG with OpenAI scripts

See RAG_Openai.md for details

Langsmith quick hands on

See Langsmith.md for details

Langsmith LLM evaluation with labeled imported datasets

See Langsmith.md for details