Pinned Repositories
advanced_functional_eda
exploratory data analysis
amazon_review_sorting
Amazon dataset review sorting
association_rule_learning
If you need the helpers.py script, please download the helpers.py file from the hybrid recommender systems repository.
crm_analytics
With the Recency Frequency Monetary analysis and customer lifetime value analysis, the csv file of our loyal customers is output.
data_science_handbook
Python Data Science Handbook: full text in Jupyter Notebooks
flow_charts
Basic flow chart studies with the flowgorithm program
git_github_cheatsheet
Git&GitHub CheatSheet
hybrid_recommender_systems
The hybrid recommendation system, which is a combination of user-based and item-based recommendation systems, is discussed. I wish you good work
ipython_notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
yaml_file_usage
Tasks being worked on and structures
kanberburak's Repositories
kanberburak/advanced_functional_eda
exploratory data analysis
kanberburak/crm_analytics
With the Recency Frequency Monetary analysis and customer lifetime value analysis, the csv file of our loyal customers is output.
kanberburak/amazon_review_sorting
Amazon dataset review sorting
kanberburak/association_rule_learning
If you need the helpers.py script, please download the helpers.py file from the hybrid recommender systems repository.
kanberburak/data_science_handbook
Python Data Science Handbook: full text in Jupyter Notebooks
kanberburak/flow_charts
Basic flow chart studies with the flowgorithm program
kanberburak/git_github_cheatsheet
Git&GitHub CheatSheet
kanberburak/hybrid_recommender_systems
The hybrid recommendation system, which is a combination of user-based and item-based recommendation systems, is discussed. I wish you good work
kanberburak/ipython_notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
kanberburak/yaml_file_usage
Tasks being worked on and structures
kanberburak/python_list_vs_numpy
The code that we can test the speed difference between using python lists and numpy.
kanberburak/regular_expressions
These are regular expressions in which we write code in accordance with the pattern writing rules with regex101, capture the desired words and lines from the irregular data, and use the code compiled to be used in the ide of the desired programming language with the code generator.
kanberburak/virtual_environment
create virtual environment, pip: pypi (python package index) package management tool, conda: package and venv management tool (anaconda repository)
kanberburak/voice_command
Command knowledge used to give voice commands via computer terminal can be enhanced with additions.