This course will take you through the process of predictive analytics/predictive modeling. A statistical technique or machine learning algorithm is borrowed to help predict an outcome. The goal of this course is to start you on your journey to becoming a top data scientist. To do that, you need to understand the methodology or methods at your disposal in solving these problems. By using a famous example (the titanic disaster), we will show you how to understand the problem in-front of you, how to explore your data, pre-process your data, how to create your first model, how to improve model accuracy, and look at some evaluation metrics.

The Hidden Markov Model or HMM is all about learning sequences. A lot of the data that would be very useful for us to model is in sequences. Stock prices are sequences of prices. Language is a sequence of words. Credit scoring involves sequences of borrowing and repaying money, and we can use those sequences to predict whether or not you're going to default.

Deep Learning is part of a broader family of machine learning methods based on learning data representations. Deeplearning4j is a Deep Learning programming library written in Java and the Java Virtual Machine (JVM) and is a computing framework with wide support for Deep Learning algorithms. In this course, you start by installing Deep Learning software for Java. You learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. The course will take you into Neural Networks, working with Perceptron, XOR, and Gradient Descent on code examples.

If you are looking for a complete course on Python programming, then go for this Learning Path. Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide speed, safety, and scalability. We will begin this learning journey by understanding the basic concepts of Python such as statements and syntax along with using numbers, strings, and tuples. We will then explore various function definition techniques along with learning the basics of classes and objects.

Artificial intelligence is yet to become a standard in schools, but it has the potential to transform the educational field. It's is a technology whose time has certainly come because it can already outperform humans in many ways. However, it can be very helpful for tech students. Meeting the needs of each student becomes a must in today's classroom. For example, a teacher should create personalized tasks to fit the learning style of students and ensure that they enjoy the same access to learning.

About this course: This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google services are currently unavailable in China).

Learning Objectives - In this module you will learn about the Recommendation platforms and implement a Recommender using MapReduce. Topics - User based recommendation, User Neighbourhood, Item based Recommendation, Implementing a Recommender using MapReduce, Platforms: Similarity Measures, Manhattan Distance, Euclidean Distance, Cosine Similarity, Pearson's Correlation Similarity, Loglikihood Similarity, Tanimoto, Evaluating Recommendation Engines (Online and Offline), Recommendors in Production.

This course lays the foundation from which you can begin using Python to solve any problem - whether in Data Analysis, Machine Learning or Web Development. It gives you a fundamental understanding of Python loops, data structures, functions, classes and more to help you solve basic programming tasks so that you can confidently apply those skills to solve real problems. The course assumes zero prior experience with Python, though some fundamental knowledge of programming is recommended.

Scala has emerged as an important tool for performing various data analysis tasks efficiently. This video will help you leverage popular Scala libraries and tools and perform core data analysis tasks with ease. This course will introduce you to Deeplearning4j; you will start with tasks such as integrating with Spark and Linear Regression with Deep Learning. Then you will make use of popular Scala libraries such as Breeze to plot your data. There is also a special focus on using Bokeh to plot your data.

Python Guide for the Total Beginner LiveLessons is an introduction to programming in Python. Students will learn not only about the basics of programming and how to work with Python, they will delve into advanced concepts, such as object oriented programming, working with database, developing for the web, and creating games. Katie Cunningham is a Python developer and author of Teach Yourself Python in 24 Hours. She's a frequent teacher, not only at conferences, but at events geared towards improving diversity in the open source arena and increasing the number of children exposed to programming. The lessons are split into six parts.