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IMPORTANCE OF DATA SCIENCE 1. Data science helps brands to understand their customers in a much enhanced and empowered manner.  2. It allows brands to communicate their story in such a engaging and powerful manner. 3. Big Data is a new field that is constantly growing and evolving.  4. Its findings and results can be applied to almost any sector like travel, healthcare and education among others.  5. Data science is accessible to almost all sectors

 Data analysis   is the process of collecting, cleansing, interpreting, transforming and modeling data to gather insights and generate reports to gain business profits. Refer to the image below to know the various steps involved in the process. Fig 1:  Process of  Data Analysis – Data Analyst Interview Questions Collect Data:  The data gets collected from various sources and is stored so that it can be cleaned and prepared. In this step, all the missing values and outliers are removed. Analyse Data:  Once the data is ready, the next step is to analyze the data. A model is run repeatedly for improvements. Then, the model is validated to check whether it meets the business requirements. Create Reports:  Finally, the model is implemented, and then reports thus generated are passed onto the stakeholders.

  Python Class Method Decorator @classmethod In Python, the  @classmetho  decorator is used to declare a method in the class as a class method that can be called using  ClassName.MethodName() . The class method can also be called using an object of the class. The  @classmethod  is an alternative of the  classmethod()  function. It is recommended to use the  @classmethod  decorator instead of the function because it is just a syntactic sugar. @classmethod Characteristics Declares a class method. The first parameter must be  cls , which can be used to access class attributes. The class method can only access the class attributes but not the instance attributes. The class method can be called using  ClassName.MethodName()  and also using object. It can return an object of the class. The following example declares a class method. class Student : name = 'unknown' # class attribute def __init__ ( self ) : ...

  Difference between SQL and MySQL Below are some key differences between SQL Vs MySQL Parameter SQL MYSQL Definition SQL is a Structured Query Language. It is useful to manage relational databases. MySQL is an RDBMS to store, retrieve, modify and administrate a database using SQL. Complexity You need to learn the SQL language to use it effectively. It is readily available through download and installation. Type SQL is a query language. MySQL is database software. It used the "SQL" language to query the database. Support for connector SQL does not provide connectors. MySQL offers an integrated tool called 'MySQL workbench' to design and develop databases. Purpose To query and operate database system. Allows data handling, storing, modifying, deleting in a tabular format. Usage SQL code and commands are used in various DBMS and RDMS systems including MYSQL. MYSQL is used as an RDBMS database. Updates The language is fixed, and the command remains the same. Get the freq...

  What is MYSQL? MySQL was one of the first open-source databases available in the market. Today there are many alternatives variants of MySQL ,. However, the differences between the variants are not significant as they use the same syntax, and basic functionality also remains the same. MySQL is an RDBMS that allows keeping the data that exists in a database organized.  MySQL  is pronounced as "My S-Q-L," but it is also called "My Sequel." It is named after co-founder Michael Widenius' daughter. MySQL provides multi-user access to databases. This RDBMS system is used with the combination of PHP and Apache Web Server, on top of a Linux distribution. MySQL uses the SQL language to query the database.

  What is SQL? SQL is a language that is used to operate your database. SQL is the basic language used for all databases. There are minor syntax changes amongst different databases, but the basic SQL syntax remains largely the same. SQL is a short abbreviation of  Structured Query Language . According to ANSI (American National Standards Institute), SQL is the standard language to operate a relational database management system. SQL is used in the accessing, updating, and manipulation of data in a database. Its design allows for the management of data in an RDBMS, such as MYSQL. SQL language is also used for controlling data access and for the creation and modification of database schemas .

  Introduction to Transfer Learning We, humans, are very perfect in applying the transfer of knowledge between tasks. This means that whenever we encounter a new problem or a task, we recognize it and apply our relevant knowledge from our previous learning experiences. This makes our work easy and fast to finish. For instance, if you know how to ride a bicycle and if you are asked to ride a motorbike which you have never done before. In such a case, our experience with a bicycle will come into play and handle tasks like balancing the bike, steering, etc. This will make things easier compared to a complete beginner. Such leanings are very useful in real life as it makes us more perfect and allows us to earn more experience. Following the same approach, a term was introduced  Transfer Learning  in the field of machine learning. This approach involves the use of knowledge that was learned in some task, and apply it to solve the problem in the related target task. While most ...

  Random Forest Regression in Python Every decision tree has high variance, but when we combine all of them together in parallel then the resultant variance is low as each decision tree gets perfectly trained on that particular sample data and hence the output doesn’t depend on one decision tree but multiple decision trees. In the case of a classification problem, the final output is taken by using the majority voting classifier. In the case of a regression problem, the final output is the mean of all the outputs. This part is Aggregation. A Random Forest is an ensemble technique capable of performing both regression and classification tasks with the use of multiple decision trees and a technique called Bootstrap and Aggregation, commonly known as  bagging . The basic idea behind this is to combine multiple decision trees in determining the final output rather than relying on individual decision trees. Random Forest has multiple decision trees as base learning models. We rando...

  Decision Tree Decision Tree: The decision  tree is the most powerful and popular tool for classification and prediction. A Decision tree is a flowchart-like tree structure, where each internal node denotes a test on an attribute, each branch represents an outcome of the test, and each leaf node (terminal node) holds a class label.    A decision tree for the concept plays tennis.   Construction of Decision Tree :   A tree can be  “learned”  by splitting the source set into subsets based on an attribute value test. This process is repeated on each derived subset in a recursive manner called  recursive partitioning . The recursion is completed when the subset at a node all has the same value of the target variable, or when splitting no longer adds value to the predictions. The construction of a decision tree classifier does not require any domain knowledge or parameter setting, and therefore is appropriate for exploratory knowledge discov...