Oleta  Becker

Oleta Becker

1600839540

Case Study: Breast Cancer Classification Using a Support Vector Machine

In this tutorial, we’re going to create a model to predict whether a patient has a positive breast cancer diagnosis based on several tumor features.

Problem Statement

The breast cancer database is a publicly available dataset from the UCI Machine learning Repository. It gives information on tumor features such as tumor size, density, and texture.

**Goal: **To create a classification model that looks at predicts if the cancer diagnosis is benign or malignant based on several features.

Data used: Kaggle-Breast Cancer Prediction Dataset

#data-science #machine-learning #support-vector-machine #python #kaggle

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Buddha Community

Case Study: Breast Cancer Classification Using a Support Vector Machine
Oleta  Becker

Oleta Becker

1600839540

Case Study: Breast Cancer Classification Using a Support Vector Machine

In this tutorial, we’re going to create a model to predict whether a patient has a positive breast cancer diagnosis based on several tumor features.

Problem Statement

The breast cancer database is a publicly available dataset from the UCI Machine learning Repository. It gives information on tumor features such as tumor size, density, and texture.

**Goal: **To create a classification model that looks at predicts if the cancer diagnosis is benign or malignant based on several features.

Data used: Kaggle-Breast Cancer Prediction Dataset

#data-science #machine-learning #support-vector-machine #python #kaggle

Java Questions

Java Questions

1595676000

Case Study: Breast Cancer Classification Using a Support Vector Machine

In this tutorial, we’re going to create a model to predict whether a patient has a positive breast cancer diagnosis based on several tumor features.

Problem Statement

The breast cancer database is a publicly available dataset from the UCI Machine learning Repository. It gives information on tumor features such as tumor size, density, and texture.

**Goal: **To create a classification model that looks at predicts if the cancer diagnosis is benign or malignant based on several features.

Data used: Kaggle-Breast Cancer Prediction Dataset


Step 1: Exploring the Dataset

First, let’s understand our dataset:

#import required libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
#import models from scikit learn module:
from sklearn.model_selection import train_test_split
from sklearn import metrics
from sklearn.svm import SVC
#import Data
df_cancer = pd.read_csv('Breast_cancer_data.csv')
df_cancer.head()
#get some information about our Data-Set
df_cancer.info()
df_cancer.describe()
#visualizing data
sns.pairplot(df_cancer, hue = 'diagnosis')
plt.figure(figsize=(7,7))
sns.heatmap(df_cancer['mean_radius mean_texture mean_perimeter mean_area mean_smoothness diagnosis'.split()].corr(), annot=True)
sns.scatterplot(x = 'mean_texture', y = 'mean_perimeter', hue = 'diagnosis', data = df_cancer)

#data-science #machine-learning #support-vector-machine #python #kaggle

Shardul Bhatt

Shardul Bhatt

1620797149

Python for Freight Forwarding: Proven Case Study for Logistics Company

Python is a popular web development language for enterprise and customer-centric applications. It is one of the top programming languages, according to TIOBE’s index. It has applications in web development, Machine Learning, Data Science, and other domains. The versatility of Python web development makes it the perfect language for applications in every project.

Amidst the hundreds of languages for web application development, Python stands out. It is powerful, scalable, and easy-to-learn. Python’s capabilities are useful in every sector — technology, FinTechHealthTechfreight forwarding industry, and more. The core functionality of Python takes care of all the programming tasks for every feature that needs to be added.

In this article, we will focus on the major aspects of Python that make it suitable for web applications of all kinds. We will then highlight the proficiency of Python using a proven case study that Python developers at BoTree have built. It is a freight forwarding software for international logistics service provider that uses Python in the main technology stack.

Checkout Top 10 real-world Python Use Cases and Applications

Let’s look at the case study and capabilities of Python in detail.

Why choose Python for Web Development

Python is now the first choice for web development, Unlike Ruby on Rails, it offers more flexibility in the process, Here are a few reasons why companies should choose Python for web development -

  • Readable: Python has an easily readable syntax. It is similar to the english language. Python developers admire the programming language as it is easy to read, write, and understand. You don’t have to write additional code to express concepts with ease. The emphasis on code readability, which enables you to maintain and update the code.
  • Multi-programming paradigms: Like all the other object-oriented and open-source programming languages, Python supports multi-programming paradigms. There’s a dynamic type system and automatic memory management. It simplifies the process of building large and complex enterprise scale applications.
  • Scalable: Python is highly scalable. Because of its in-built capabilities to minimize the errors during the development process, it is perfect for freight forwarding software solutions that require processing bills at a huge scale. It is also suitable for enterprise dashboards and other applications that need to handle massive server requests at once.
  • Versatile: Python is a heavily versatile programming language. It has diverse applications in various domains, including statistical analysis, numerical computations, data analytics and more. Companies can use it for web development or Machine Learning applications. Today, Python plays a crucial role in building data science models and intelligent algorithms.
  • Library
    One of the biggest reasons to choose Python is because of its library set. Python has libraries for almost everything — there’s TensorFlow, Selenium, Apache Spark, Requests, Theano, Py Torch and many more. The libraries enable adding functionalities and features, simplifying the process of building high-quality web applications.

Checkout Top Python Libraries for Data Science to use in 2020

As Python grows in popularity, its community also grows. There are more developers than any other programming language. They provide support for different development problems, support, and training for multiple projects.

Let’s look at a proven case study by BoTree Technologies that showcases Python’s capabilities in web development.

Python: Proven Case Study of a Logistics Company

At BoTree, we use Python development services for building dynamic web applications. Today we will discuss a case study on the freight forwarding services industry. We developed it using Python and other technologies. Let’s understand it better.

About the Case Study

We designed the freight forwarding software for a leading international logistics services provider. The system we created would collect the information from different freight forwarding websites using bill of lading or the container number. The information is then entered into the centralized system automatically for better management of the freight.

The main challenge was the manual processing of bills of lading. The information had to be gathered from a large number of websites. Each website had hundreds and thousands of bills. The manual process was lengthy and time-consuming. Because the freight forwarding companies were based out of different geographical locations, the client also faced language barriers while processing the B/L.

Our Technology Stack

The technology stack to add freight forwarding features was simple and powerful. We used Python, Postgresql, AWS SQS, EC2m, Puppeteer and Virtual Private Cloud. We offered web development, software testing, and continuous support and maintenance.

The technology stack we used was focused on simplifying the complications in the freight forwarding system. Because the solution had to be scalable, Python was the probably choice for building the web application.

Our Solution

We built a fully server-les architecture. It performs the mapping of the websites and analyzes the different fields for assessing the required details in freight forwarding.

The solution parses data from different websites and matches the fields with the required information. It also takes into account previously parsed data for making the decision.

The collected information is structurally arranged into a format. The entire data system is then pushed back to a centralized ERP system. All the data is accumulated at a single place, making it easier to process the B/L without any hassle.

The freight forwarding solution consisted of the following features built using Python -

Core Features

  • B/L Processing: The system could easily parse 15000 B/L in a single day.
  • Efficiency delivery: The process became efficient by 30% for processing the B/L.
  • Activity log maintenance: There’s a proper record of all the records that take place in the system.
  • Multiple languages: The freight forwarding software could easily parse B/L in different languages.

Conclusion

Python is a powerful programming language for enterprise-grade applications. Logistics companies heavily benefit from investing in freight forwarding solutions. Shipping systems are essential for managing the timely delivery of products and services. An internal system for B/L processing can enable you to reap the benefits of swift deliveries.

BoTree Technologies is a custom software development company that has Python experts who can build quality applications for enterprises. We have experience in the logistics, healthcare, fintech, education, and multiple other industries.

Connect with us today for a FREE CONSULTATION in the next 24 hours!

Originally published at https://www.botreetechnologies.com on May 11, 2021.

#python case study for logistics company #b/l processing system #freight forwarding case study #logistics case study #case study for logistics company #python web development

Multiclass Classification with Support Vector Machines

Support Vector Machines (SVM) are not new but are still a powerful tool for classification due to their tendency not to overfit, but to perform well in many cases. If you are only interested in a certain topic, just scroll over the topics. These are the topics in chronological order:
What’s the mathematical concept behind the Support Vector Machine?
What is a kernel and what are kernel functions?
What is the kernel trick?
What is the dual problem of a SVM?
How does Multiclass Classification take place?
Implementation via Python and scikit-learn
If you are only interested in how it can be implemented using Python and scikit-learn, scroll down to the end!

#scikit-learn #classification #python #support-vector-machine #machine-learning

Ashish parmar

Ashish parmar

1604480711

Case study on mobile app; DreamG

Dream-G application will allow user to chat, voice calls and video calls to random people through the mobile application. The User can create a profile and perform all these actions in addition to searching for a person using their name.

Client Requirement
The client came with the requirement of developing a unique mobile application for users to chat with others and make voice and video calls. Furthermore, the user should be able to subscribe to the plan by paying a certain amount.

App Features and Functionalities
The User can see the list of the people and able to view the profile of a particular person and able to chat, voice call, and video call.
The user can see the list of entertainers and can chat, Voice call and Video call them.
User can search for any person by entering the name.
Through the chat option, the user can see the past history of the chat with all the users. The user can also open any chat and again send messages.
The user can see the profile details and able to edit or modify the profile photo, name, and other details. The user can see the call log details.
The user can see the number of coins available with them and through these coins, the user will able to make voice and video calls.
The user can purchase the plan listed in the application according to the requirements, and will be able to chat with the people.
The User can refer the mobile application to other people and earn rewarding coins.

Challenges
To create a unique user experience for the Chat, Voice, and Video Calls.

Technical Specification & Implementation
Integration with the payment Gateway
Android: Android Studio with Java
Solution
We successfully developed and implemented the Dream-G mobile application through which the user will able to chat, voice call, and video call to other people. The user will also be able to purchase the subscription plan and refer the application to other people.

Read more: https://www.prismetric.com/work/dreamg-app/

#case #study #case-study-on-mobile-app #mobile-app-case-study