Develop-Packt's repositories
Employing-Python-s-Tools-with-Statistics
This module covers the formal topic of statistics and its relevant concepts. It covers a number of theoretical discussion points and examples and hands-on coding activities to help understand theory.
Introduction-to-Workflow-Management-Platform-Airflow
In this module, you will look at creating a pipeline by breaking down a job into multiple executable stages. You will implement a simple linear pipeline and then move further by implementing a multi-stage data pipeline, then automate the multi-stage pipeline using Bash. Further to this you will improve the efficiency by running the pipeline as an asynchronous process using the ETL workflow and then create DAG for the pipeline and implement it using Airflow.
Tracking-Objects
Track an object of your choice using various filters and algorithms available in OpenCV.
Using-OpenVINO-and-OpenCV
Explore the OpenVINO toolkit, focusing on components like model zoo, inference engine, and model optimizer, and how they can be used to perform deep learning and computer vision tasks.
Applying-Foundational-Probability-Concepts
This module covers probability theory and looks at how you can use NumPy and SciPy to solve probability problems.
Beginning-Calculus-with-Python
This module covers derivatives and integrals and how Python can be used to perform basic calculus.
Building-an-Artificial-Intelligence-Algorithm
Learn how to build a machine learning mode and get started on the popular deep learning framework PyTorch. You will delve into one of the most exciting fields in deep learning research - reinforcement learning - and take a closer look at the deep Q-learning algorithm
Detecting-Facial-Images
Practice face detection and tracking in image and video frames, isolating features such as skin or eyes with specialized techniques.
Developing-Pythons-Use-in-Statistics
This module presents some of the most useful concepts in inferential statistics, and covers confidence intervals and hypothesis testing.
Exploring-and-Visualizing-Statistics-with-Python
This module will cover the main descriptive statistics metrics and learn how to produce visualizations used in exploratory data analysis.
Extending-Calculus-with-Python
You will use derivatives and integrals to find maximum and minimum values in functions using Python.
Extending-Mathematics-with-Python
This module covers the mathematical system called Markov Chains and how you can implement Markov Chains using a transition matrix to solve complex problems.
Handling-Big-Data-File-Formats
You will look at the different formats for storing, transmitting and organizing very large collections of data. You will learn how to choose the right data formats as well as look at compression.
Introduction-to-Analytics-Engine-Spark-for-Big-Data
Discover the fundamentals of Apache Spark, including its architecture, transformations and actions. Learn why the design choices of RDD were made and how this enhances the Hadoop and MapReduce construct.
Introduction-to-Computer-Vision-and-Image-Processing
This chapter covers the Amazon Rekognition service for analyzing the content of the images using various techniques. You will learn how to analyze faces and recognize celebrities in images. You will also be able to compare faces in different images to see how closely they match with each other.
Introduction-to-Conversational-Artificial-Intelligence
This module teaches you how to design a chatbot using Amazon Lex by following the best design practices for conversational AI. You will start by learning the basics of chatbots. Then, you will use Amazon Lex to create a custom chatbot that gets the latest stock market quotes by recognizing the intent in text
Introduction-to-Data-Storage
In this module, you will explore the broad range of capabilities of AI, and see some of the fields that it is changing. You will build your first AI system, and look at optimization.
Introduction-to-Data-Storage-on-Cloud-Services-AWS
Here you will cover the pros and cons of various cloud data storage solutions. You will create, access, and manage your Amazon S3 cloud services. Learn how to use the AWS Command Line Interface (CLI) and Python Software Development Kit (SDK) to control Amazon Web Services (AWS). Lastly, you will create a simple data pipeline that reads from and writes to your cloud data storage.
Introduction-to-Data-System-Design
You will look at some existing system designs and analyze the reasons for specific design choices. The module will also cover how to design AI systems with some cases from designing general-purpose data storage systems too.
Introduction-to-Deep-Q-Learning
The module covers different Q learning algorithms using Open AI and FrozenLake.
Introduction-to-Python-Structures-and-Tools
Review the basic Python tools and data structures before applying your new skills by using loops, functions, lists and more to solve problems.
Introduction-to-the-Ethics-of-AI-Data-Storage
You will look at several case studies, examining everything from AI being used to manipulate elections, to AI displaying racial and sexist prejudices. Implement a simple sentiment classifier to differentiate between positive and negative words and sentences. You'll observe how this works in many cases, and display the problematic biases and human stereotypes in the classifier.
Mathematics-with-Python
This module covers sequences and series as well as exploring trigonometry, vectors, and complex numbers to give a basis for a number of applications from engineering to finance.
Practicing-Calculus-with-Python
In this module you will use derivatives and integrals to solve more complicated Calculus problems and see how to find Taylor Series, polynomials that approximate complicated trigonometric and exponential functions.
Understanding-Python-s-Main-Tools-in-Statistics
This module presents a practical introduction to the main libraries that most statistics practitioners use in Python. It will cover some of the most important and useful tools used for statistics and calculus in Python.
Updating-Data
This module focuses on data preparation for AI projects. This involves data cleaning, and any other data preparation work that is commonly involved and required by data engineers.
Using-Functions-and-Algebra-with-Python
This module covers functions, the building blocks of mathematics. It will look at how functions and algebra can be utilized in Python.
Using-Speech-with-the-Chatbot
This module looks at how use Amazon Connect, Lex, and Lambda to interact with a chatbot using voice. You will create a personal call center using Amazon Connect and you will learn how to connect the call center to your Lex chatbot
Working-with-Contours
Detect and handle contours in OpenCV to prepare for object tracking.
Working-with-Data-Stores-SQL-and-NoSQL-Databases
We will look at SQL and NoSQL databases and decide the ideal database to be used based on the format of data. Then you will implement storing and querying data in different databases such as MySQL, MongoDB, and Cassandra.