To make a library of functions that are frequently used for data anlaysis and machine learning tasks
1. MatrixDeterminantF :
> determinant_f
x determinant_2
x determinant_3plus
> is_square_matrix
> round_off_f
> inverse_f
x identity_matrix
x zero_matrix
1. dot_product
2. element_wise_operation
3. matrix_multiplication
4. pad_with_zero
5. print_a_matrix
6. shape_changer
7. transpose
8. vector_addition
9. make_matrix_float
10. make_vector_float
11. round_off_f
12. unique_values
13. value_counts
14. is_numerical
15. min_max_f
16. type_of
17. element_wise_matrix_operation
18. matrix_vector_product_f
19. split_vector
1. MultivariantLinearRegression :
> multivariant_linear_regression
x generate_score
> batch_gradient_descent
x mse_cost_function
> hash_to_table
x train_test_split
x randomize
1. coefficient
2. convert_and_impute
3. covariance
4. impute_string
5. mean
6. read_csv
7. root_mean_square
8. simple_linear_regression_prediction
9. variance
10. convert_string_categorical
11. normalize_vector_f
12. logistic_function_f
13. log_gradient_f
14. logistic_predict
15. randomize_vector_f
16. randomize_f
17. train_test_split_vector_f
18. train_test_split_f
19. correlation
20. std_dev
21. spearman_rank
1. LayerDetails :
> create_weights
> create_bias
> output_of_layer
1. activation_leaky_relu
2. activation_relu
3. activation_sigmoid
1. StringToMatch :
> compare_percentage
x calculate
> clean_string
x char_vector
> compare_chars
> compare_position
> fuzzy_subset
x n_gram
> split_alpha_numericals
> char_count
> frequent_char
> char_replace