Zainab Ashimiyu-Abdusalam

@zheeburg for a traceback error, try deleting your runtime and disconnect. Then run your code all over from the start. I think the problem should've resolved.

On it @GemmaTuron Link to the Colab [here](https://colab.research.google.com/drive/1UGkv-AKZSXWmKBnqE7CQUdFEvfIcbOfs?usp=sharing)

### Table of Content - [x] Dataset Overview [ ] What are we trying to predict? - [x] Stage 1 - Data Upload [ ] How many data points do...

### Data Overview; Bioavailability dataset from TDC Bioavailability can be categorized under absorption of drugs and it's the fraction of an administered drug that becomes available at the site of...

### Stage 1 - Data Upload The **TDC Bioavailability ** dataset contains 640 drugs. The dataset was downloaded from **TDC** after its installation and then divided into the 3-way split...

### Stage 2 - Data Analysis The data analysis of the **Bioavailability dataset** gave us a deep insight into the data and the kind of results to expect. _**Is this...

### Data Modelling & Model Training This stage involves creating a list of data that is used to train, validate and test our model. Our data make up of 3...

### Model Evaluation (METRIC 1) The binary classifier was evaluated based on the following metrics; - **AUROC Value & ROC Curve**; The AUC represents the degree of separability and tells...

### Model Evaluation (METRIC 2) - **Contingency Table**; This is also known as the Confusion matrix. This table is used to assess errors made while the model is predicting. **The...

### Model Evaluation (Metric 3) - **Precision;** Quantifies the number of correct positive predictions made i.e. What proportion of positive identifications was actually correct. It is calculated as  Note;...