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Avijeet is a Senior Research Analyst at Simplilearn. Passionate about Data Analytics, Machine Learning, and Deep Learning, Avijeet is also interested in politics, cricket, and football.
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Lessons in Coding
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Welcome to python.
Front matter, how to use this book.
Preparing data is half the battle, finding the meaning, visualizing data, practice problems, back matter, authors and affiliations.
A.J. Henley
Bibliographic information.
Book Title : Learn Data Analysis with Python
Book Subtitle : Lessons in Coding
Authors : A.J. Henley, Dave Wolf
DOI : https://doi.org/10.1007/978-1-4842-3486-0
Publisher : Apress Berkeley, CA
eBook Packages : Professional and Applied Computing , Apress Access Books , Professional and Applied Computing (R0)
Copyright Information : A.J. Henley and Dave Wolf 2018
Softcover ISBN : 978-1-4842-3485-3 Published: 23 February 2018
eBook ISBN : 978-1-4842-3486-0 Published: 22 February 2018
Edition Number : 1
Number of Pages : IX, 97
Number of Illustrations : 15 illustrations in colour
Topics : Python , Data Mining and Knowledge Discovery , Big Data , Big Data/Analytics
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A case study in data science is an in-depth analysis of a real-world problem using data-driven approaches. It involves collecting, cleaning, and analyzing data to extract insights and solve challenges, offering practical insights into how data science techniques can address complex issues across various industries.
This repository is a companion to the textbook Case Studies in Neural Data Analysis, by Mark Kramer and Uri Eden. That textbook uses MATLAB to analyze examples of neuronal data. The material here is similar, except that we use Python. The intended audience is the practicing neuroscientist - e.g., the students, researchers, and clinicians ...
All of the data science case studies mentioned below are solved and explained using Python. Case Study 1: ... Use Case: Customer Personality Analysis is a detailed analysis of a company's ideal ...
Data analysis is a broad term that covers a wide range of techniques that enable you to reveal any insights and relationships that may exist within raw data. As you might expect, Python lends itself readily to data analysis. Once Python has analyzed your data, you can then use your findings to make good business decisions, improve procedures, and even make informed predictions based on what ...
A Case study in python. Creating an ML model to predict the apt price of a given diamond. Predicting the right price for an old car using python machine learning. Create an ML model to forecast the demand of rental bikes every hour of the day. Estimating the price of a computer, based on its specs.
This project is a collection of six captivating case studies that use Python and computational techniques to analyse data, build classification models and unravel insights on multifaceted datasets. The array of topics touch on different domains of knowledge. Central to these studies is the application of tools and concepts.
All of the data science case studies mentioned below are solved and explained using Python. Case Study 1: ... Use Case: Customer Personality Analysis is a detailed analysis of a company's ideal customers. It helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs ...
Most of the functions used here are the same in Python 2 and 3. One noteable exception however is division. If you are using Python 2, you will find that the division operator / actually computes the floor of the division if both operands are integers (i.e., no decimal points). For example, in Python 2, 4/3 equals 1. While, in Python 3, 4/3 ...
Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive.
Above code will load the dataset to 'data'. The 'Attrition' column is our dependent variables and others are independent. The one thing to note here is that 'Attrition' take value ...
182SHARES. Author: Tim Dobbins Engineer & Statistician. Author: John Burke Research Analyst. Statistics. Essential Statistics for Data Science: A Case Study using Python, Part I. Get to know some of the essential statistics you should be very familiar with when learning data science. LearnDataSci is reader-supported.
Analyze Traffic Safety Data with Python. Visualize traffic safety data and analyze the relationship between collisions and smartphone usage over time. Meet the creator of the course. Meet the full team. Andrea Hassler. Andrea has a Master's in Applied Statistics from NYU and a Bachelor's in Psychology from SUNY New Paltz.
Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)
A Data Science Case Study with Python: Mercari Price Prediction. ... In this case study, we will walk through the Analysis, Modelling and Communication part of the workflow. The general steps involved for solving a data science problem are as follows: ... did exploratory data analysis, feature transformations and finally selected ML models, did ...
1. Sentiment Analysis. The first project of this list is to build a machine learning model that predicts the sentiment of a movie review. Sentiment analysis is an NLP technique used to determine whether data is positive, negative, or neutral.
This creates a case-study approach that simulates the working conditions you'll experience in real-world data science projects. You'll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning ...
This course is part of the Statistics with Python Specialization. When you enroll in this course, you'll also be enrolled in this Specialization. Learn new concepts from industry experts. Gain a foundational understanding of a subject or tool. Develop job-relevant skills with hands-on projects.
Data Analytics Using Python Libraries, Pandas and Matplotlib. We'll use a car.csv dataset and perform exploratory data analysis using Pandas and Matplotlib library functions to manipulate and visualize the data and find insights. 1. Import the libraries. 2. Load the dataset using pandas read_csv () function.
This case study highlights how using SQL (and Python) for data analysis allows for discovering trends and insights of particular statistical interest. The case study is based on historical data ...
To prepare data for analysis, here's what we do: #import libraries. import pandas as pd. import seaborn as sns. In Python, it's usual to add "as something" when you import the library. This makes the code less lengthy when you call the libraries. Next, we need data.
This code is a common initial step in data analysis using Python, where these modules are often used for data manipulation, analysis, and visualization. ... Syntax Code Explanation from Case Study ...
Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Pythonalso helps you discover meaning in the data using analysis and shows you how to visualize it.