Commercial enterprises, web developers, financial institutions, and e-commerce businesses are all taking notice of how machine learning (ML) can provide a competitive advantage. Through applying computer technology and sophisticated algorithms to growing datasets of customer information, predictive analysis can reveal what customers are interested in, and are likely to purchase.
Historical data can be utilized to target future markets. To determine why past initiatives have met with less than glorious success, and predict reaction to new products and services.
Why Python?
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Python has taken a leading role in development of machine learning functionality, for a number of reasons:
- World-wide acceptance as a programming language that is strategically positioned for data sciences
- Simplicity in coding structure – generate functions with fewer actual lines of code
- Wealth of forums, formal training courses, and texts for individualized learning
- Considerable body of code samples, algorithms, and libraries readily available – at no cost
In short, Python functions can be garnered from a wide variety of sources. Thus resulting in applications for machine learning that provide faster and more accurate results for programming projects.
Getting Started with Python Project Ideas
So now that you have a piqued interest in learning Python. Let’s unleash the power of machine learning, how do you begin? To start, there’s no shortage of applications for machine learning technology.
Pick a topic you’re interested in or one that may be of value to your employer (or prospective employer). Search the web for sample datasets. You may be surprised at the variety available at no cost. Some more current than others, but many are relevant for Python projects, especially for beginners. Sports, social media, weather, retail, marketing, and finance are all out there to select from.
Python Code Examples
You need not have a degree in computer science to get started with Python applications. There are so many existing forums and resources for code examples that you can build a great deal of functionality through reusing libraries and code others have made available to you.
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Scikit-learn is one such resource, starting off with some basic terms and definition of Python terms:
- Classification
- Clustering
- Regression
- Model selection
- Pre-processing
- Dimensionality reduction
Sound complicated? Scikit-learn will not only explain these concepts, but will provide examples of code that can be reused as open source, making the examples free for personal or even commercial use. Updates and new contributions are added on a regular basis.
Reddit is another site worth investigating for anything related to Python development, including:
- Forums and commentary from developers of every level
- Python algorithms, scripts, and code examples to share
- Python tricks and tips – updated frequently
- Even news of career opportunities through a Python job board
- Much more
GitHub is a collaboration of literally millions of developers and businesses where code and applications can be shared, reviewed, and discussed for suggestions and improvements. Programming challenges for Python developers are also offered for testing your skills.
These sites are certainly not limited to developers, but also include Javascript functions, games, applications, and much more. Participation is welcome for all levels of interest: beginners, students, business developers, and educators.
Examples of Python Code
Getting started with coding should include either an introductory-level course (classroom or online are both very effective), or alternatively downloading/purchasing a book that has received kudos from successful Python developers.
Analyzing every command and its syntax is not the most effective goal for a new developer. It’s much more important to get hands-on experience to comprehend the concepts and technology behind Python and machine learning. In-depth knowledge and coding skills come with time, experience, and real-life projects.
That said, there are a plethora of coding examples at your disposal on-line. Searching for best coding practices and tips will reveal solutions to both basic programming questions and suggestions for solving complex functions.
Python3.codes provides beginners and experts alike with sample coding and development challenges, games, and adventures into artificial intelligence.
Ubuntu forums are loaded with coding examples contributed by Python developers of varying skill levels, providing insight to multiple approaches for solving programming challenges.
Python Alternatives
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While Python is currently the odds-on favorite for machine learning and data science, there are alternatives that also enjoy a high level of popularity:
Java has been around for many years, and there is a significant population of skilled Java developers. Here too, there are many forums, web sites, and open source examples to browse for code that suits your needs. Or at least gets you started on the right path.
Many reusable algorithms for machine learning can be applied to Javascript programming, building on existing Java skills to generate machine learning and deep learning functionality.
Java project ideas follow the same basic criteria as with Python or any language:
- Select a topic that is meaningful or interesting to you or your business problem
- Start with the basics – get some initial training or personal reading on Java development
- Get coding – use tools such as online examples and programming guidelines. First tackle a simple project to grasp the basics, then build complexity as you gain experience and confidence in your abilities.
Other development alternatives include:
- R – a leading choice for machine learning functionality, although recently losing ground to Python
- C and C++ – popular with the legions of C and C++ developers world-wide
- Julia – many developers view Julia to be a rising star for developers, but time will tell
Regardless of the programming platform and project you pursue, applying best practices and standards garnered from web sources, formal training, and professionally-written texts can lead to a rewarding experience and a profitable career opportunity.
