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Data Science and Deep Learning Workshop For Scientists and Engineers
WORKSHOP 1: In this workshop, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on recognizing traffic signs using GTSRB dataset, detecting brain tumor using Brain Image MRI dataset, classifying gender, and recognizing facial expression using FER2013 dataset In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, Pandas, NumPy and other libraries to perform prediction on handwritten digits using MNIST dataset with PyQt. You will build a GUI applicatio...
FULL SOURCE CODE: PRACTICAL DATA SCIENCE WITH MYSQL AND PYTHON GUI
In this project, we provide you with the MySQL version of SQLite sample database named chinook. The chinook sample database is a good database for practicing with SQL, especially SQLite. The detailed description of the database can be found on: https://www.sqlitetutorial.net/sqlite-sample-database/. There are 11 tables in the chinook sample database:The employee table stores employees data such as employee id, last name, first name, etc. It also has a field named ReportsTo to specify who reports to whom; customers table stores customers data; invoices & invoice_items tables: these two tables store invoice data. The invoice table stores invoice header data and the invoice_items table stores t...
ZERO TO MASTERY: THE COMPLETE GUIDE TO LEARNING SQLITE AND PYTHON GUI
In this project, we provide you with the SQLite version of The Oracle Database Sample Schemas that provides a common platform for examples in each release of the Oracle Database. The sample database is also a good database for practicing with SQL, especially SQLite. The detailed description of the database can be found on: http://luna-ext.di.fc.ul.pt/oracle11g/server.112/e10831/diagrams.htm#insertedID0. The four schemas are a set of interlinked schemas. This set of schemas provides a layered approach to complexity: A simple schema Human Resources (HR) is useful for introducing basic topics. An extension to this schema supports Oracle Internet Directory demos; A second schema, Order Entry (OE...
DATA SCIENCE WORKSHOP: Parkinson Classification and Prediction Using Machine Learning and Deep Learning with Python GUI
In this data science workshop focused on Parkinson's disease classification and prediction, we begin by exploring the dataset containing features relevant to the disease. We perform data exploration to understand the structure of the dataset, check for missing values, and gain insights into the distribution of features. Visualizations are used to analyze the distribution of features and their relationship with the target variable, which is whether an individual has Parkinson's disease or not. After data exploration, we preprocess the dataset to prepare it for machine learning models. This involves handling missing values, scaling numerical features, and encoding categorical variables if nece...
DATA ANALYSIS USING JDBC AND SQL SERVER WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE
This book is SQL SERVER version of our previous book titled “DATA ANALYSIS USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE”. In this project, you will use the SQL VERSION version of Northwind database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, shi...
DATA SCIENCE WORKSHOP: Chronic Kidney Disease Classification and Prediction Using Machine Learning and Deep Learning with Python GUI
In the captivating journey of our data science workshop, we embarked on the exploration of Chronic Kidney Disease classification and prediction. Our quest began with a thorough dive into data exploration, where we meticulously delved into the dataset's intricacies to unearth hidden patterns and insights. We analyzed the distribution of categorized features, unraveling the nuances that underlie chronic kidney disease. Guided by the principles of machine learning, we embarked on the quest to build predictive models. With the aid of grid search, we fine-tuned our machine learning algorithms, optimizing their hyperparameters for peak performance. Each model, whether K-Nearest Neighbors, Decision...
DATA ANALYSIS USING JDBC AND POSTGRESQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE
This book is PostgreSQL version of our previous book titled “DATA ANALYSIS USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE”. In this project, you will use the PostgreSQL version of Northwind database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, ship...
HOTEL REVIEW: SENTIMENT ANALYSIS USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI
The data used in this project is the data published by Anurag Sharma about hotel reviews that were given by costumers. The data is given in two files, a train and test. The train.csv is the training data, containing unique User_ID for each entry with the review entered by a costumer and the browser and device used. The target variable is Is_Response, a variable that states whether the costumers was happy or not happy while staying in the hotel. This type of variable makes the project to a classification problem. The test.csv is the testing data, contains similar headings as the train data, without the target variable. The models used in this project are K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier, and LSTM. Three vectorizers used in machine learning are Hashing Vectorizer, Count Vectorizer, and TFID Vectorizer. Finally, you will develop a GUI using PyQt5 to plot cross validation score, predicted values versus true values, confusion matrix, learning curve, performance of the model, scalability of the model, training loss, and training accuracy.
IMAGE STEGANOGRAPHY Least Significant Bit (LSB) with AES, DES, RSA, ECC, and ELGAMAL Cryptosystem: LEARN BY EXAMPLES WITH PYTHON AND TKINTER
In the rapidly evolving field of digital security, image steganography has emerged as a vital technique for embedding secret information within digital images, ensuring both privacy and data integrity. "IMAGE STEGANOGRAPHY: Least Significant Bit (LSB) with AES, DES, RSA, ECC, and ELGAMAL Cryptosystem: LEARN BY EXAMPLES WITH PYTHON AND TKINTER" delves into the intricate world of steganography, exploring how the Least Significant Bit (LSB) method can be employed in conjunction with robust cryptographic algorithms to enhance data concealment. This book provides a comprehensive guide to integrating classic and modern encryption techniques, including AES, DES, RSA, ECC, and ElGamal, within the re...
SYMMETRIC KEY CRYPTOGRAPHY WITH PYTHON AND TKINTER
In the evolving landscape of data security, encryption algorithms play a crucial role in safeguarding sensitive information. This book delves into several prominent encryption algorithms, including AES, DES, 3DES, Blowfish, and CAST. Each algorithm offers unique strengths and is suitable for different use cases. Advanced Encryption Standard (AES) stands out for its robust security and efficiency, making it a preferred choice for many modern applications. Data Encryption Standard (DES), while historically significant, has largely been replaced by Triple DES (3DES), which enhances DES's security by applying it multiple times. Blowfish, a versatile and fast cipher, and CAST, known for its flexi...
