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Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python Martin Czygan, Phuong Vo.T.H, Ashish Kumar, Kirthi Raman - okladka książki

Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python Martin Czygan, Phuong Vo.T.H, Ashish Kumar, Kirthi Raman - okladka książki

Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python Martin Czygan, Phuong Vo.T.H, Ashish Kumar, Kirthi Raman - audiobook MP3

Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python Martin Czygan, Phuong Vo.T.H, Ashish Kumar, Kirthi Raman - audiobook CD

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You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn.
After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You’ll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling.
After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples
This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:
? Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan
•Learning Predictive Analytics with Python, Ashish Kumar
•Mastering Python Data Visualization, Kirthi Raman

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O autorach książki

Martin Czygan studied German literature and computer science in Leipzig, Germany. He has been working as a software engineer for more than 10 years. For the past eight years, he has been diving into Python, and is still enjoying it. In recent years, he has been helping clients to build data processing pipelines and search and analytics systems.
Phuong Vo.T.H has a MSc degree in computer science, which is related to machine learning. After graduation, she continued to work in some companies as a data scientist. She has experience in analyzing users' behavior and building recommendation systems based on users' web histories. She loves to read machine learning and mathematics algorithm books, as well as data analysis articles.
Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.
Kirthi Raman is currently working as a lead data engineer with Neustar Inc, based

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