Description

To make a library of functions that are frequently used for data anlaysis and machine learning tasks

Changes

Planned

  1. Testing and better documentation for all the structs and functions so far

List of Functions and Structs

lib_matrix

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

20. splitvectorat

lib_ml

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
16. train_test_split
17. correlation
18. std_dev
19. s_rank

20. howmanyand_where

lib_nn

1. LayerDetails :
    > create_weights
    > create_bias
    > output_of_layer

1. activation_leaky_relu
2. activation_relu
3. activation_sigmoid

4. activation_tanh

lib_string

1. StringToMatch :
    > compare_percentage
        x calculate
    > clean_string
        x char_vector
    > compare_chars
    > compare_position
    > fuzzy_subset
        x n_gram
    > split_alpha_numericals (update: acknowledges spaces)
    > char_count
    > frequent_char
    > char_replace

About the author

Vibliography ?