-
Hands-on Machine Learning with TensorFlow
Machine and deep learning capabilities are in demand, and Python is the fastest-growing tool in machine and deep learning. TensorFlow is a Python library for fast numerical computing created and released by Google that is used in deep learning and primarily focuses on neural networks.
more
-
Hands-on Applied Machine Learning in R
R is the one of the most popular machine learning tools in use today. This course focuses on taking concepts in machine learning and applying them in practical ways. Common algorithms such as regression, clustering, and classification are explained, applied, and evaluated using R.
more
-
Hands-on Machine Learning in R: Advanced Techniques
R is the one of the most popular machine learning tools in use today. This course focuses on taking concepts in machine learning and applying them in practical ways.
more
-
Hands-on Machine Learning with Python
Python is one of the most popular languages used in machine learning, data science, and predictive analytics. In this hands-on course, you will how to use Python, scikit-learn, and lightgbm to create regression and decision tree models. You will leave with complete code examples that you can use and build on in your own work.
more
-
Machine & Deep Learning: Delivering Insights from Big Data
Today, data is more than just a corporate asset. As data consumers, we’ve become accustomed to having up-to-the-minute analytics for any event that might affect our business or personal lives. We’re becoming used to the influence of IoT in our homes, cities, clothing, phones, and more—and the resulting instant access to analytics.
more
-
Advanced Analytics: Leveraging Data Science and Machine Learning Techniques to Gain Data Insights
Analytics encompasses many skills and disciplines. Identifying the problem, choosing the modeling approach, selecting the correct features to model, and evaluating the result are at the heart of analytics. The tendency, however, is to focus primarily on the technology rather than the process.
more
-
Introduction to Machine Learning
Machine learning encompasses many skills and disciplines. Identifying the problem, choosing the modeling approach, selecting the correct features to model, and evaluating the result are at the heart of machine learning. The tendency, however, is to focus primarily on the technology rather than the process.
more
-
Machine Learning in R
R is the one of the most popular machine learning tools in use today. This course focuses on introducing concepts in machine learning and applying them in practical ways using R. Topics include R data manipulation, data structures, R graphics, exploratory data analysis, basic statistics, and introduction to regression and classification modeling.
more
-
Hands-on Machine Learning Made Easy
In this hands-on tutorial we will provide all the fundamentals for understanding and effectively training predictive models using the mighty random forest algorithm (our personal favorite). Focusing on core concepts and intuitions means that no complicated math is required, and the R code will be a breeze, even for first-timers.
more
-
Supervised Machine Learning: Preparing Data & Deploying Analytic Models for Classification & Prediction
Regression, decision trees, neural networks—along with many other supervised learning techniques—provide powerful predictive insights. These data-driven insights inform the forces shaping your organization’s outcomes.
more