Author: Naveen
Naveen PandeyStress Detection Project using Machine Learning
Stress, tension, and misery are undermining the psychological well-being of individuals. Each individual has a justification behind having an unpleasant life. Individuals frequently discuss their thoughts via web-based entertainment stages like on Instagram as posts and stories, and on Reddit through requesting ideas about their life on subreddits. In the beyond couple of years, many…
Read MoreNumPy for Data Science – Part 5
The difference between copy and view Copy View Join & split function Join array – joining means putting contents of two or more array in a single array. hstack vs vstack The major difference is that np.hstack combines NumPy arrays horizontally and np.vstack combines arrays vertically. Split – splitting breaks one array into multiple. NumPy…
Read MoreNumPy for Data Science – Part 4
Broadcasting NumPy Arrays The term broadcasting describes how NumPy treats arrays with different shapes during arithmetic operations. Subject to certain constraints, the smaller array is “broadcast” across the larger array in order that they have compatible shapes. NumPy operations are usually done on pairs of arrays on an element-by-element basis. Within the simplest case, the…
Read MoreOutlier Detection methods in Machine Learning
Objective An outlier is an individual point of data that is distant from other points in the dataset. It is an anomaly in the dataset that may be caused by a range of errors in capturing, processing or manipulating data. Outliers in the data may cause problem during model fitting as it may inflate the…
Read MoreMissing Values Treatment methods in Machine Learning
Delete Missing Value Rows Missing values can be handled by deleting the rows or columns having null values. If columns have more than half of the rows as null then the entire columns can be dropped. The rows which are having one or more columns values as null can also dropped. Pros: A model trained…
Read MoreNumPy for Data Science – Part 3
Arithmetic Operations in NumPy Arrays In NumPy there are multiple functions which we can use to perform the arithmetic operation, we will be looking them one by one. The add() function can also be used to perform the same operation. The subtract() function can also be used to perform the same operation. The multiply() function…
Read MoreNumPy for Data Science – Part 2
Create NumPy Arrays with Random Numbers Data Types in NumPy Arrays Shape and Reshaping In NumPy Arrays Shape of an Array The shape of an array is the number of elements in each dimension. Get the Shape of an Array NumPy arrays have an attribute called shape that returns a tuple with each index having the number…
Read MoreNumPy for Data Science – Part 1
What is NumPy Array? An array is a grid of values and it contains information about the raw data, how to locate an element, and how to interpret an element. Numpy vs Python List Advantages of using NumPy Arrays over Python List: Let’s look at the example of NumPy Array and Python List. Importance of…
Read MoreRestaurant Recommendation System using Machine Learning
In this article we are going to discuss about the Restaurant Recommendation System. it is an application that recommends similar restaurants to a customer according to the customer’s taste. We will learn how to build a restaurant recommendation system. This article will take you through how to build a restaurant recommendation system using Machine Learning.…
Read MoreHotel Sentiment Analysis using NLP
Whenever we are trying to find hotels for vacation or travel, we always prefer a hotel known for its services. The simplest way to find out whether a hotel is right for you or not is to find out what people are saying about the hotel who have stayed there before. Now it’s very difficult…
Read MoreDifference between Pandas .at and .iat Function
.at The .at and .iat index accessors are analogous to .loc and .iloc. The difference being that they will return a numpy.ndarray when pulling out a duplicate value, whereas .loc and .iloc return a Series: .iat .iat is similar to [] indexing. Because it tries to support both positional and label based indexing, I advise…
Read MoreTop 10 Pandas Functions
1 – To Read CSV and Excel files. These Functions will be used in almost every Project, They are used to read a CSV or an excel file to pandas DataFrame format. 2 – Columns Function. When we have a big dataset with many columns it will be difficult to see all columns, hence we…
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