Information retrieval (VINF) - recommender school project.
- Python 3.5
- Pandas, Numpy, Sklearn libraries
- Elastic Search
Recommend activit or product for users.
df = pd.read_csv('train_activity.csv', sep=',', names=dheader)
n_users = df.user_id.unique().shape[0]
n_items = df.item_id.unique().shape[0]
print ('Number of users = ' + str(n_users) + ' | Number of items = ' + str(n_items))
train_data, test_data = cv.train_test_split(df, test_size=0.25)
train_data = pd.DataFrame(train_data)
test_data = pd.DataFrame(test_data)
- Install python on local machine
- Download data files (.csv)
- Run one of the following script without any parameters
python3 test.py
python3 main.py
- Datasource is old dataset from slovak server zlava dna