Go hands-on with the neural network, artificial intelligence, and machine learning techniques employers are seeking!
What Will I Learn?
- Develop using iPython notebooks
- Understand statistical measures such as standard deviation
- Visualize data distributions, probability mass functions, and probability density functions
- Visualize data with matplotlib
- Use covariance and correlation metrics
- Apply conditional probability for finding correlated features
- Use Bayes’ Theorem to identify false positives
- Make predictions using linear regression, polynomial regression, and multivariate regression
- Understand complex multi-level models
- Use train/test and K-Fold cross validation to choose the right model
- Build a spam classifier using Naive Bayes
- Use decision trees to predict hiring decisions
- Cluster data using K-Means clustering and Support Vector Machines (SVM)
- Build a movie recommender system using item-based and user-based collaborative filtering
- Predict classifications using K-Nearest-Neighbor (KNN)
- Apply dimensionality reduction with Principal Component Analysis (PCA) to classify flowers
- Understand reinforcement learning — and how to build a Pac-Man bot
- Clean your input data to remove outliers
- Implement machine learning, clustering, and search using TF/IDF at massive scale with Apache Spark’s MLLib
- Design and evaluate A/B tests using T-Tests and P-Values
Who is the target audience?
- Software developers or programmers who want to transition into the lucrative data science career path will learn a lot from this course.
- Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you’ll need some prior experience in coding or scripting to be successful.
- If you have no prior coding or scripting experience, you should NOT take this course — yet. Go take an introductory Python course first.
Originally published at Online Courses Best Deals.
Source: Deep Learning on Medium