**This Article Includes:**

1.Introduction

2.Real World Problem

2.1 Description

2.2 Problem Statement

2.3 Bussiness Objectives and Constraints

3.Datasets Available for Text Detection And Recognition

3.1 Dataset Overview & Description

4.Exploratory Data Analysis(EDA)

5.Methods of text detection before deep learning era

6.EAST (Efficient Accurate Scene…

Predicting Customer Satisfaction for the purchase made from the Brazilian e-commerce site Olist.

**This Article Includes:**

1.Introduction

2.Business Problem

3.Problem Statement

4.Bussiness objectives and constraints

5.Machine Learning Formulation

i Data Overview

ii.Data Description

iii.Machine Learning Problem

iv.Performance Metrics

6.Exploratory Data Analysis(EDA)

a.Data Cleaning and…

A series of programming questions were asked in interviews for daily practices.

This problem was asked by Amazon which is based on Data Compression in which **implementation of Run-Length Encoding of Strings **was asked.

**Run-length Encoding **is the simplest data compression technique. The basic idea behind this is to represent…

A series of programming questions were asked in interviews for daily practices.

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” — Martin Fowler

This is the first article of this series. In this series, you will get programming questions asked…

**Natural Language Processing** (NLP) is one of the hot areas in machine learning for research nowadays, few applications of NLP are Sentimental Analysis, Chatbots & Virtual Assistants, Text Classification & Extraction, Auto-Correction e.t.c.To …

Exploratory Data Analysis (EDA) On Olist Dataset (Brazilian E-Commerce Dataset)

**This Article Includes:**

1. Data Overview

2. Data Description

3. Reading Data(.csv)

4. Data Cleaning

* Handling missing values

* Data Deduplication

5. High Level Statistics

6. Univariate Analysis

7. Bivariate Analysis

8. Multivariate Analysis

9. RFM Analysis

10. Conclusion

**…**

Box Plot (also called as Box and Whiskers Plot) is a very popular and widely used plot for visualizing data in the field of Statistics and Data Analysis. In comparison with other graphical techniques, Box Plot not only shows the distribution/spread of data but also indicates the minimum and maximum…

As we Know, Outliers are patterns in the datasets that do not conform to the expected behaviour. It may appear in the dataset due to low-quality measurements, malfunctioning equipment, manual error e.t.c. The presence of outliers may create problems in building a good machine learning model.

There are mainly two…

NumPy library is an important foundational tool for studying Machine Learning. Many of its functions are very useful for performing any mathematical or scientific calculation. As it is known that mathematics is the foundation of machine learning, most of the mathematical tasks can be performed using NumPy.

Matplotlib is one of the most popular and oldest plotting libraries in Python which is used in Machine Learning. In Machine learning, it helps to understand the huge amount of data through different visualisations.

Now, let us explore more about Matplotlib.

Contents

1.Introduction to Matplotlib

2. How to Install?

3. How to import?

4.Understanding…