Through this tutorial, you'll learn how to migrate the movies dataset from Neo4j to Memgraph. If you used Neo4j, you are probably familiar with their example graph that helps you learn the basics of the Cypher query language. Neo4j is an ACID-compliant transactional native graph database, while Memgraph is a platform designed for graph computations on streaming data. You can read more about their differences in the Neo4j vs Memgraph article. If you're having trouble running this on the new Apple M1 chip, try adding --platform linux/arm64/v8 after the run command.

Welcome to Feature Selection for Machine Learning, the most comprehensive course on feature selection available online. In this course, you will learn how to select the variables in your data set and build simpler, faster, more reliable and more interpretable machine learning models. Who is this course for? You've given your first steps into data science, you know the most commonly used machine learning models, you probably built a few linear regression or decision tree based models. You are familiar with data pre-processing techniques like removing missing data, transforming variables, encoding categorical variables.

Simply put, training data is a dataset that is used to train a machine learning model. The purpose of training data is to provide the model with examples of how it should behave in different situations. Without training data, it would be very difficult for machines to learn how to perform specific tasks. In this article, we will discuss why training data is important for AI and computer vision, and we will provide some tips on where you can find high-quality training datasets. Training data is important for AI and computer vision because it allows machines to learn from examples.

Have a fundamental understanding of the Python programming language. Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc.. Understand how to create your own Python programs. Become a Python Expert Have the skills and understanding of Python to confidently apply for Python programming jobs. Proudly add the Python Object-Oriented Programming (OOP) skills to your résumé. Learn Python from experienced professional software developers.

Learn how to build and deploy data science applications in Python. Analyzing data and building machine learning models is one thing. Packaging these analyses and models such that they are sharable is a different ball game altogether. This course aims at teaching you the fastest and easiest way to build and share data applications using Streamlit. You don't need any experience in building front-end applications for this.

Artificial Intelligence (AI) is intelligence exhibited by machines. In Computer Science, AI research deals with how to create computers that are capable of intelligent behavior. AI has been defined in numerous ways, but in general, it can be described as a way of making a computer system "smart" – able to understand complex tasks and carry out complex commands. The principal benefit of AI is that it can help humans make better decisions by providing insights and recommendations informed by data. AI has several applications and is being employed in a growing number of industries, including healthcare, finance, manufacturing, and transportation. Some of the most remarkable applications of AI are in the field of robotics, where AI is used to create machines that can carry out complex tasks.

This course will teach you about image processing, classification, and how robots with computer vision can interact with pictures with python and OpenCV, and later you will transform this program into a web application and deploy it on the cloud. You will learn in this course: Computer vision and its various applications. Create a computer vision program with python and OpenCV.

The field of deep learning has been growing exponentially in recent times, mostly due to the huge amount of data that is available and easily accessible computing resources, in this blog we are going to discuss what deep learning actually is, why to use deep learning, and how to get started with it so basically it will provide you the complete roadmap to be a deep learning engineer with books attached. "Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans" Deep learning is a series of algorithms that attempts to imitate the learning of a human brain, or at least that's what they claim, what actually happens inside is that it performs several complex mathematical functions that make it possible for a computer to perform a task like humans. For example, we have seen driverless cars well deep learning is the key technology behind this miracle, we can talk to our phone and issue a command and it will do said task, eg Siri, Amazon Alexa, well deep learning makes all of this possible. Through deep learning, a computer model learns to perform classification tasks directly from images, text, or audio. Deep learning algorithms can achieve state-of-the-art accuracy, even exceeding human-level performance from time to time.

Are you completely beginner or intermediate in data science and confused about what kind of questions you may get asked in the interview? Preparing for your next data science interview and wants to boost up your confidence before the interview? Then this is the course for YOU! Now as we all know data science is the most in-demand skill of the 21st century. Then, you should definitely think of enrolling in this course and complete all the practice tests from important areas of data science like machine learning, statistics, SQL, etc. before your interview. This course covers practice tests from important areas of data science like machine learning, python, statistics, etc.

Get 21st century's #1 Job: The Most Comprehensive Data Science Course from highly experienced Barton Poulson Learn Data Science: Full Course for Beginners Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! Learn from experienced Data scientist, Barton Poulson. This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost!