Towards Machine Learning

                                          Variables Variables is a container which stores the values in it. Every values in Python has a datatype. Datatypes in Python are numbers, list, tuple, strings, dictionary etc. Rules for Python Variables A Variable name can contain alpha-numeric characters and underscores (A - Z , a - z, _). A Variable name can start with number or underscore character, but can' t start with a number. Variable name should not be keywords. Keywords are some specific names that are used in Python for some specific function. Variable names in Python are case sensitive. (Height, height, HEIGHT are different). Variable Declaration Here we didn't defined data type , as we know Python is dynamically typed so not required to define explicitly.     Multiple Variable Declaration           We can declare multipl...

                               Time and Work Time and Work is a another important concepts in aptitude. Pipes and cistern is an application of time and work. Time and Work is directly proportional , where if work increases, time also increases. Work and person is directly proportional, where if  work increases , persons also increases. Time and Person is inversely proportional , where if person increases ,time decreases. Formulas : If `A` completes work in `n` days , then the work completed in one day is 1/n th part of work. If `A` completes 1/n th work in one day, then total work completed in `n` days. Let us assume `A` completes the work in `n` days and `B` completes the work in `m` days .Let us take work as only one unit, the amount of work done in one day by `A` is 1/n similarly for `B` is 1/m. So in how many days the work is completed if they work together then ,A + B = 1/n + 1/m. Problem...

 Introduction  Python is developed by Guido Van Rossum and released in 1991. Python is high level, interpreted, general purpose programming language. It is one of the top five most used languages in the world. Currently there are 8.2 million developers who code in Python. Python is one of the most preferred languages in the field of Data Science and Artificial Intelligence. Key Features Python is an interpreted language, unlike compiled languages like Java, C, C++, C#, Go etc., Python codes are executed directly even before compiling.  Python is Dynamically typed, no need to mention type of variable before assigning. Python handles it without raising any error. Python codes can be executed on different software or operating systems without changing it. Python supports both Functional and Object oriented programming as it supports creating classes and objects. Python has high number of modules and frameworks support. Python is free and Open Source, which means it is availa...

                                         Module - 1 The best practice,  while solving the problems on percentage is to calculate 50% , 10% and 1%. Examples :  1. For 500 Ans : For 50% is                          50/100 * 500 = 250              For 25% is                         25/100 * 500 = 125             For 10% is                         10/100 * 500 = 50             For 1% is                          1/100 * 500 = 5 Simple ways is   For 50% , value is...

                                    Percentage This is most important topic which helps to solve in profit and loss, simple interest , compound interest etc. As name says per cent means per 100. It means we need to calculate everything per hundred. The value between 0 to 100 . % is the symbol is used to denote percentages. In Exams sometimes you will be asked to calculate percentage but options will be given in fractions and vice versa. Let us solve some problems converting percentage into fractions and vice versa. 1. Represent 25%  into fraction. Ans :             This means 25 is out of 100.  The percentage value is should be divided by 100.                                  25/100 = 1/4            ...

                          Data  Preprocessing Data Preprocessing is a technique that is used to convert the raw data into a clean data set. In other words, whenever the data is gathered from different sources it is collected in raw format which is not feasible for the analysis. Need of Data Preprocessing Inaccurate data There are many reasons for missing data such as data is not continuously collected, a mistake in data entry, technical problems with bio-metrics and much more. The presence of noisy data The reasons for the existence of noisy data could be a technological problem of gadget that gathers data, a human mistake during data entry and much more. Inconsistent data  The   presence of inconsistencies are due to the reasons such that existence of duplication within data, human data entry, containing mistakes in codes or names, i.e., violation of data constraints and much more. Steps Involved ...