Learning Path - Deep Dive into Python Machine Learning

Description:

Confidently take your data mining and machine learning skills to your work

The world is emitting data at an enormous rate. There is a need for professionals who can confidently work with data and output meaningful insight. Data Science is a rewarding career field that allows you to solve some of the world's most interesting problems. This Learning Path will give you hands-on experience with popular Python data mining and machine learning algorithms. First, we'll expand your knowledge base by covering basic to advanced concepts of Python. Then, we'll give you hands-on experience with the popular Python data mining algorithms. Going forward, we'll learn how to perform various machine learning tasks in the real world. Finally, we'll dive into the future of data science and implement intelligent systems using deep learning with Python.

Basic knowledge:

Basic knowledge on Python. Aimed at Python programmers and data scientists who are willing to learn data mining and machine learning algorithms.

Who this course is for:

Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course. Technologists curious about how deep learning really works 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.

Course Completion Certificate

What will you learn:

• Get to grips with the basics of operating in a Python development environment
• Build Python packages to efficiently create reusable code
• Become proficient at creating tools and utility programs in Python
• Use the Git version control system to protect your development environment from unwanted changes
• Harness the power of Python to automate other software
• Distribute computation tasks across multiple processors
• Handle high I/O loads with asynchronous I/O to get a smoother performance
• Take advantage of Python's metaprogramming and programmable syntax features
• Get acquainted to the concepts behind reactive programming and RxPy
• Understand the basic data mining concepts to implement efficient models using Python
• Know how to use Python libraries and mathematical toolkits such as numpy, pandas, matplotlib, and sci-kit learn
• Build your first application that makes predictions from data and see how to evaluate the regression model
• Analyze and implement Logistic Regression and the KNN model
• Dive into the most effective data cleaning process to get accurate results
• Master the classification concepts and implement the various classification algorithms
• Explore classification algorithms and apply them to the income bracket estimation problem
• Use predictive modeling and apply it to real-world problems
• Understand how to perform market segmentation using unsupervised learning
• Explore data visualization techniques to interact with your data in diverse ways
• Find out how to build a recommendation engine
• Understand how to interact with text data and build models to analyze it
• Work with speech data and recognize spoken words using Hidden Markov Models
• Analyze stock market data using Conditional Random Fields
• Work with image data and build systems for image recognition and biometric face recognition
• Grasp how to use deep neural networks to build an optical character recognition system
• Get a quick brief about backpropagation
• Perceive and understand automatic differentiation with Theano
• Exhibit the powerful mechanism of seamless CPU and GPU usage with Theano
• Understand the usage and innards of Keras to beautify your neural network designs
• Apply convolutional neural networks for image analysis
• Discover the methods of image classification and harness object recognition using deep learning
• Get to know recurrent neural networks for the textual sentimental analysis model

Simpliv LLC, a platform for learning and teaching online courses. We basically focus on online learning which helps to learn business concepts, software technology to develop personal and professional goals through video library by recognized industry experts or trainers.

Why Simpliv

With the ever-evolving industry trends, there is a constant need of the professionally designed learning solutions that deliver key innovations on time and on a budget to achieve long-term success.

Simpliv understands the changing needs and allows the global learners to evaluate their technical abilities by aligning the learnings to key business objectives in order to fill the skills gaps that exist in the various business areas including IT, Marketing, Business Development, and much more.