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Python for Machine Learning
Master the skills to use machine learning in your day-to-day work with this Python course. Create algorithms to predict classes, continuous values, and more.
How to Become a Data Scientist
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written by Pierian Training founder Jose Portilla!
What You’ll Learn
- You will learn how to use data science and machine learning with Python.
- Understand Machine Learning from top to bottom.
- Learn NumPy for numerical processing with Python.
- Conduct feature engineering on real world case studies.
- Learn Pandas for data manipulation with Python.
- Create supervised machine learning algorithms to predict classes.
- Create regression machine learning algorithms for predicting continuous values.
- Construct a modern portfolio of machine learning resume projects.
- Learn how to use Scikit-learn to apply powerful machine learning algorithms.
- Get set-up quickly with the Anaconda data science stack environment.
- Understand the full product workflow for the machine learning lifecycle.
- Explore how to deploy your machine learning models as interactive APIs.
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Course Content
This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Machine Learning. With a focus on SciKit Learn, you’ll learn all aspects of Machine Learning ranging from a variety of regression types (Linear / Lasso /Ridge), Elastic Net, K Nearest Neighbors and Means Clustering, Hierarchal Clustering, DBSCAN, PCA, and Model Deployment.
- Python
- Jupyter notebooks
- Numpy
- Pandas
- Matplotlib
- Machine Learning concepts
- Supervised vs Unsupervised Learning
- Types of Machine Learning – Classification vs Regression
- Evaluation
- Machine Learning Methods – All in Theory and Practice
- Linear Regression
- Logistic Regression
- K Nearest Neighbors
- Support Vector Machine
- Decision Trees
- Unsupervised Learning Methods
- Feature Engineering and Data Preparation
Experienced Python developers looking to understand a wide variety of machine learning algorithms, including supervised and unsupervised learning algorithms.
Course Description
This machine learning course is designed for experienced python developers who want to learn the theory and application of a large variety of machine learning methods. Starting from simple linear regression, this training takes students through a tour of the most popular machine learning models used in practice. The course focuses on teaching students how to unlock the power of the Scikit-Learn Python library. Students will learn how to choose a model, train the model on data, and evaluate and tune the model for deployment.
Instructor-Led
Learn directly from our expert instructors via live webinar. Also includes the full video-on-demand course.
On-Demand
Get access to this self-paced Python for Machine Learning training course plus the entire Pierian on-demand course catalog with a Data Science Hero membership.
Starting at
$99
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