Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Then this course is for you! This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
This course is all about A/B testing. A/B testing is used everywhere. A/B testing is all about comparing things. If you're a data scientist, and you want to tell the rest of the company, "logo A is better than logo B", well you can't just say that without proving it using numbers and statistics. Traditional A/B testing has been around for a long time, and it's full of approximations and confusing definitions.
One of the most common problems learners have when jumping into Machine Learning and Data Science is the steep learning curve, and when you add to this the complexity of learning programming languages like Python or R you can get demotivated and lose interest fast. In this course you will learn the basic concepts of machine learning using a visual tool. Where you can just drag drop machine learning algorithms and all other functionality hiding the ugliness of code, making it much more easier to grasp the fundamental concepts. I will "hand-hold" you as we build from scratch 2 different types of supervised machine learning algorithms used in the real world, across several industries and I will explain where and how they are used. The course will teach you those fundamental concepts by implementing practical exercises which are based on live examples.
Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! 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!
Go hands-on with the neural network, artificial intelligence, and machine learning techniques employers are seeking! Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive course includes over 80** lectures** spanning 12** hours of video**, and most topics include hands-on Python code examples you can use for reference and for practice. I'll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn't.
In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE. After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a spam detector.
Get the foundation in business analysis you need to solve your organization's biggest problems. This course provides everything you need to get started in your career in business analysis. Our courses focus on how analysis is performed in the real world, and they're full of examples, case studies and lessons learned from actual Business Analysts on the job. This is a perfect first course in any business analysis curriculum.
Stanford University's Machine Learning Course Andrew Ng is the man. The founder of Google Brain and former chief scientist at Baidu, Andrew Ng's course is the clear winner in terms of ratings, reviews, and syllabus fit. Seeing how this course was what practically founded Coursera, that doesn't seem unbelievable. Although it has a smaller scope than the original Stanford class, it covers a large number of algorithms and techniques. The estimated timeline is eleven weeks, which includes two weeks of neural networks and deep learnings.
WIRE)--Jul 30, 2018--MapR Technologies, Inc., provider of the industry's leading data platform for AI and Analytics, today announced a new, free introductory course from MapR Academy on Artificial Intelligence (AI) and Machine Learning (ML). This on-demand course provides insights into how businesses can leverage AI and ML to improve operations through real-world use cases. This course is ideal for developers just starting out in ML, as well as higher-level business decision makers. "Machine learning, a trending topic in big data, is not fully understood. This course provides a foundation for anyone curious about ML/AI and how it works in practical applications," said Suzanne Ferry, vice president, global training and enablement, MapR.
Data Science A-Z: Real-Life Data Science Exercises Included by Kirill Eremenko will help you learn Data Science step by step through real analytics examples, Data Mining, Modeling, Tableau Visualization and more. This Data Science course is absolutely perfect for beginners. You will learn everything you need to get a Data Science job and make a good salary. This Data Science video tutorial will teach you how to perform Data Mining in Tableau. You will learn how to clean and prepare your data for analysis.