Save hours of browsing through the Internet and accelerate your workflow with code-ready templates for your programming projects. Personally crafted by 365 Data Science instructors, these templates bring a surprising efficiency level to your work process.

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Importing the Pandas Library in Python

This template demonstrates how to import the pandas library in Python- a popular open-source library that provides high-performance structures and data analysis tools. Some other related topics you might be interested in are Indexing in Pandas Python, Using Attributes in Python, Using Pandas Methods for Working with Series Objects in Python, and Creating DataFrames in Python. The Importing the Pandas Library in Python is among the topics covered in detail in the 365 Program.

This free open-access template shows how to convert date and time values between the different time zones in Python. Some other related topics you might be interested in are Local Time and Universal Time in Python, Importing the Pandas Library in Python, Creating a Series Object by Using a NumPy Array in Python, and Using Attributes in Python. The Converting Timezones in Python template is among the topics covered in detail in the 365 Program.

This is an open-access template demonstrating how to estimate the local time and compare it to universal time in Python. Some other related topics you might be interested in are Converting Timezones in Python, Converting between Timezones in DataFrames, Importing the Pandas Library in Python, and Creating a Series Object from a List in Python. The Local Time and Universal Time in Python template is among the topics covered in detail in the 365 Program.

The following template teaches you one way to convert an image file to an array (tensor). This is extremely useful in ML and Computer Vision, as these fields require images as data, however, the algorithms can only work with numbers and arrays. Some other related topics you might be interested in are Tensorboard - Tracking Metrics in Python, Tensorboard - Confusion Matrix in Python, Tensorboard - Tuning Hyperparameters in Python, and A Simple CNN Network - Convolutional Layer in Python. The Converting Images into Arrays in Python is among the topics covered in great detail in the 365 Data Science Program.

This template demonstrates how one can tune the hyperparameters of their network model using TensorBoard. Hyperparameter tuning is important aspect of Machine Learning and being able to do it automatically can be a time saver. TensorBoard provides other visualization options, as well. Some other related topics you might be interested in are Dropout in Python, L2 Regularization and Weight Decay in Python, Converting Images into Arrays, and A Common CNN Architecture in Python. The TensorBoard – tuning Hyperparameters in Python.

The confusion matrix is an essential tool when trying to solve classification problems. There are many different ways to construct such a matrix. In the following template we show you how one can create and visualize the confusion matrix with the help of TensorBoard and sklearn. Some other related topics you might be interested in are TensorBoard - Tuning Hyperparameters in Python, Converting Images into Arrays, L2 Regularization and Weight Decay in Python, and Dropout in Python. The TensorBoard template is among the topics covered in detail in the 365 Program.

The following is a program used to demonstrate how to log different metrics in Tensorboard for visualization later. An example CNN network is used. The TensorBoard callback is defined to log the loss function and accuracy during training. Then, the extension is loaded in order to visualize these metrics. Some other related topics you might be interested in are TensorBoard - Confusion Metrics in Python, TensorBoard - Tuning Hyperparameters in Python, Converting Images into Arrays. The TensorBoard - Tracking Metrics in Python template is among the topics covered in the 365 Data Science Program.

Convolutional Neural Networks are a powerful choice for problems and datsets involving images. However, they can grow to become so big, that training it on a normal system takes too long. So, the following template shows a particular network architecture that can be very effective for most problems, but is also small enough to be trained quickly. Some other related topics you might be interested in are Pooling Layers in Python, Tensorboard - Tracking Metrics in Python, Tensorboard - Confusion Metrics in Python, and Tensorboard - Tuning Hyperparameters in Python. The Common CNN Architecture in Python template is among the topics covered in detail in the 365 Program.

Pooling Layers are an important part of a Convolutional Neural Network (CNN). That's why, the following template demonstrates how one can add a MaxPooling layer to the network architecture, as well as discuss the important parameters that need to be considered and included. Some other related topics you might be interested in are Simple CNN Network - Convolutional Layer in Python, A Common CNN Architecture in Python, TensorBoard - Tracking Metrics in Python, and Tensorboard - Tuning Hyperparameters in Python. The Pooling Layers in Python template is among the topics covered in detail in the 365 Program.

A Simple CNN Network - Convolutional Layer in Python

This template demonstrates how one can add convolutional layers to our network in order to create a Convolutional Neural Network (CNN).. Some other related topics you might be interested in are Pooling Layers in Python, A Common CNN Architecture in Python, Tensorboard - Tracking Metrics in Python, and Tensorboard - Tuning Hyperparameters in Python. The template is among the topics covered in detail in the 365 Program

In this template you will find a list of the most commonly used regular expressions as well as a link to the Python documentation website, where the full list is stored. We will start with a simple example demonstrating the function of the compile(), match(), and search() methods. After that, more complicated regular expressions are constructed. Some other related topics you might be interested in are String formatting in Python, Bubble Sort in Python, Linear search in Python, Binary Search in Python. The Regular Expressions in Python template is among the topics covered in detail in the 365 Data Science Program.

The following template demonstrates how to implement an insertion sort function in Python. Some other related topics you might be interested in are Bubble sort in Python, Linear search in Python, Binary search in Python, and Sets and operations with sets in Python. The Insertion Sort in Python is among the topics covered in detail in the 365 Data Science Program

The following notebook demonstrates how to implement a binary search function(also knows as half interval) in Python. Some other related topics you might be interested in are Bubble sort in Python, Linear search in Python, and Sets and operations with sets in Python. The Binary Search in Python is among the topics covered in detail in the 365 Data Science Program

The following Jtemplate demonstrates how to implement a linear search function in Python. Some other related topic you might be interested in Bubble sort in Python, Insertion sort in Python, Binary search in Python, Sets and operations with sets in Python are Bubble Sort in Python, Insertion Sort in Python, Binary Search in Python, Sets and Operations with Sets in Python. The Linear Search in Python template is among the topics covered in detail in the 365 Data Science Program.

The following template demonstrates the difference between lists and sets in Python, and includes examples. Some other related topics you might be interested in are Linear search in Python, Binary search in Python, Insertion sort in Python, Bubble sort in Python. The Set and Operations with Sets in Python Template is among the topics covered in detail in the 365 Data Science Program.

The following notebook demonstrates how to iterate through a list more effectively using the enumerate() built-in function in Python. Some other related topics you might be interested in are The zip function in Python, Defining functions in Python - the Fibonacci sequence, Recursion in Python - the Fibonacci sequence and Defining Classes in Python. The Enumerate Function in Python template is among the topics covered in detail in the 365 Data Science Program.

Writing a Text on Top of an Image with PIL in Python

The following notebook demonstrates how to put a text on a picture having a specific position, font and color. Some other related topics you might be interested in are Line and Scatterplots with matplotlib in Python, Opening and Displaying an Image with PIL and Matplotlib in Python, Cropping an Image with PIL in Python, Resizing an image with PIL in Python, Converting a Color image to Grayscale with PIL in Python, Blurring an Image with PIL in Python. The Writing a Text on Top of an Image with PIL in Python template is among the topics covered in the 365 Data Science Program.

The following notebook demonstrates how to blur an image to a desired extend with the help of the PIL library in Python. This is done by making use of a certain image filter. A link to a list of all image filters in the PIL library is provided. Some other related topics you might be interested in are Line and Scatterplots with matplotlib in Python, Opening and Displaying an Image with PIL and Matplotlib in Python, Cropping an Image with PIL in Python, Resizing an Image with PIL in Python, Converting a Color Image to Grayscale with PIL in Python, Writing a Text on Top of an Image with PIL in Python. The Blurring an Image with PIL in Python template is among the topics covered in detail in the 365 Data Science Program.

Converting a Color Image to Grayscale with PIL in Python

The following notebook demonstrates how to convert a colored image into a grayscale one with the help of the PIL library in Python. This is done by applying a certain conversion mode. A link to a list of all conversion modes is also provided. Some other related topics you might be interested in are Line and Scatterplots with matplotlib in Python, Opening and Displaying an image with PIL and Matplotlib in Python, Cropping an Image with PIL in Python, Resizing an Image with PIL in Python, Blurring an Image with PIL in Python, Writing a Text on Top of an Image with PIL in Python. The Converting a Color Image to Grayscale with PIL in Python template is among the topics covered in detail in the 365 Data Science Program.

The following template demonstrates how to resize an image in Python given height and width. Some other related topics you might be interested in are Data Analysts, Data Scientists, Data Architects, Data Engineers, Big Data Engineers, Big Data Architects, BI Developers, Machine Learning Engineers and more. The Resizing an Image with PIL in Python template is among the topics covered in detail in the 365 Data Science Program.

Check out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.

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Obtaining Descriptive Statistics about the Data in Python

The following template demonstrates how to obtain an overview about the dataset. It shows the application of the .describe() method on a pandas Series object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Data Selection in Python, and Common Attributes for Working with DataFrames in Python. The Obtaining Descriptive Statistics about the Data in Python template is among the topics covered in detail in the 365 Program.

Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts.
Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.

This Normal Distribution in Excel template demonstrates that the sum of 2 randomly thrown dice is normally distributed.
Open the .xlsx file with Microsoft Excel. Study the structure of the file and experiment with different values.
Some other related topics you might be interested to explore are Positive Skew in Excel, Zero Skew in Excel, Negative Skew in Excel, Uniform Distribution in Excel, Standard Normal Distribution in Excel
You can now download the Excel template for free.
Normal Distribution in Excel is among the topics covered in detail in the 365 Data Science program

Common Attributes for Working with DataFrames in Python

The following template demonstrates the application of important pandas attributes when cleaning, preprocessing, and analyzing a dataset. Some other related topics you might be interested in are Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Using Pandas Methods for Working with Series Objects in Python. The Common Attributes for Working with DataFrames in Python template is among the topics covered in detail in the 365 Program.

Check out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.

Templatespython

Obtaining Descriptive Statistics about the Data in Python

The following template demonstrates how to obtain an overview about the dataset. It shows the application of the .describe() method on a pandas Series object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Data Selection in Python, and Common Attributes for Working with DataFrames in Python. The Obtaining Descriptive Statistics about the Data in Python template is among the topics covered in detail in the 365 Program.

Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts.
Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.

This Normal Distribution in Excel template demonstrates that the sum of 2 randomly thrown dice is normally distributed.
Open the .xlsx file with Microsoft Excel. Study the structure of the file and experiment with different values.
Some other related topics you might be interested to explore are Positive Skew in Excel, Zero Skew in Excel, Negative Skew in Excel, Uniform Distribution in Excel, Standard Normal Distribution in Excel
You can now download the Excel template for free.
Normal Distribution in Excel is among the topics covered in detail in the 365 Data Science program

Common Attributes for Working with DataFrames in Python

The following template demonstrates the application of important pandas attributes when cleaning, preprocessing, and analyzing a dataset. Some other related topics you might be interested in are Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Using Pandas Methods for Working with Series Objects in Python. The Common Attributes for Working with DataFrames in Python template is among the topics covered in detail in the 365 Program.