This Track covers essential topics in data engineering such as understanding data engineering, software engineering principles, cloud computing, and data visualizations. You'll gain hands-on experience in data importation, data cleaning, and optimizing your code for efficiency. You'll also learn the ...
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 5h 26m | Size: 581 MB Get up and running with the basics of Python before progressing to more advanced topics specific to data engineering. In this hands-on, interactive course, join instructor Deepak Goyal to...
It covers topics such as deploying to production, versioning and monitoring.Online you find some false information that versioning and automated deployment wouldn't be possible with NiFi but this book shows how it's done!AirflowIn this book Airflow is also introduced and you're shown how to ...
In the first module of the Python for Data Science course, learners will be introduced to the fundamental concepts of Python programming. The module begins with the basics of Python, covering essential topics like introduction to Python.Next, the module delves into working with Jupyter notebooks, ...
Data Science Data Engineering Python Blenda GuedesBlenda is a full-stack data practitioner, from modeling and building data warehouses through running machine learning models to building dashboards. Topics Data Science Data Engineering Python Exploratory Data Analysis in Python for Absolute Beginners Getti...
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height1.1float (short for floating) birth_year2001int (short for integer) There are many more data types, but as a start, knowing these four will good enough and the rest will come along the way. It’s important to know that in Python every variable is overwritable. Eg. if we now ru...
and computer vision makes it the primary choice in the domain of Artificial Intelligence. This course is primarily designed with the "learn by doing" philosophy. A simplified explanation of the topics, real-world analogies, codes being built from scratch, exhaustive demonstrations and numerous hands...
A new treatment of classic machine learning topics, such as classification, regression, and time series analysis from a Bayesian perspective. It is a must read for people who intends to perform research on Bayesian learning and probabilistic inference. Graphical Models, Exponential Families, and ...