New to the world of data science and machine learning? Welcome to your ultimate guide and starting point, whether you’re looking to break into the industry, learn something new, or hone your current skills. The Back to Basics: 5-Step Introduction series is all you need and is designed to turn complex concepts into simple, straightforward insights.
As part of KDnuggets’ 30-year journey within the data science, machine learning and artificial intelligence space, the team has come together to curate a variety of articles for you to soak up all the knowledge you can.
When you start something new, it is always difficult to get started. The KDnuggets team is taking that weight off your shoulders with our Back to Basics: Getting Started in 5 Steps series, including:
- Python data structures
- SQL
- Scientific learning
- PyTorch
- Google cloud platform
So let’s get right into it…
This tutorial covers the fundamental data structures of Python: lists, tuples, dictionaries, and sets. Learn its features, use cases and practical examples, all in 5 steps.
When it comes to learning how to program, regardless of the particular programming language you use for this task, you will find that there are a few important topics in your newly chosen discipline that most of what you are exposed to could be classified as.
Some of them, in the general order of assimilation, are syntax (the vocabulary of the language); commands (gather vocabulary in a useful way); flow control (how we guide the order of command execution); algorithms (the steps we take to solve specific problems… how did it become such a confusing word?); and finally, data structures (the virtual storage repositories we use for data manipulation during the execution of algorithms (which are, again… a series of steps).
Learn the 5 steps: Getting started with Python data structures in 5 steps
This comprehensive SQL tutorial covers everything from setting up your SQL environment to mastering advanced concepts like joins and subqueries, and optimizing query performance. With step-by-step examples, this guide is perfect for beginners looking to improve their data management skills.
When it comes to managing and manipulating data in relational databases, Structured Query Language (SQL) is the biggest name in the game. SQL is an important domain-specific language that serves as a cornerstone for database management and provides a standardized way to interact with databases.
With data being the driving force behind decision-making and innovation, SQL remains an essential technology that demands high-level attention from analysts, developers, and data scientists.
Learn the 5 steps: Getting started with SQL in 5 steps
This tutorial provides a complete hands-on tour of machine learning with Scikit-learn. Readers will learn key concepts and techniques including data preprocessing, model training and evaluation, hyperparameter tuning, and joint model compilation to improve performance.
By learning to use Scientific learningObviously, we must have an existing understanding of the underlying concepts of machine learning, as Scikit-learn is nothing more than a practical tool for implementing machine learning principles and related tasks. Machine learning is a subset of artificial intelligence that allows computers to learn and improve from experience without being explicitly programmed. Algorithms use training data to make predictions or decisions by discovering patterns and information.
Learn the 5 steps: Getting started with Scikit-learn in 5 steps
This tutorial provides a detailed introduction to machine learning using PyTorch and its high-level wrapper, PyTorch Lightning. The article covers essential steps from installation to advanced topics, offers a practical approach to building and training neural networks, and emphasizes the benefits of using Lightning.
PyTorch is a popular open source machine learning framework based on Python and optimized for GPU-accelerated computing. Originally developed by Meta ai in 2016 and now part of the Linux Foundation, PyTorch has quickly become one of the most widely used frameworks for deep learning research and applications.
Unlike other frameworks like TensorFlow, PyTorch uses dynamic calculation graphs that allow for greater flexibility and debugging capabilities.
Learn the 5 steps: Getting started with PyTorch in 5 steps
Explore the basics of Google Cloud Platform for data science and machine learning, from setting up accounts to deploying models, with practical project examples.
This article aims to provide a step-by-step overview on how to get started using Google cloud platform (GCP) for data science and machine learning. We’ll provide an overview of GCP and its key analytics capabilities, explain account setup, and explore essential services such as Great consultation and Cloud storageCreate a sample data project and use GCP for machine learning.
Whether you’re new to GCP or looking for a quick refresher, read on to learn the basics and get started with Google Cloud.
Learn the 5 steps: Getting started with Google Cloud Platform in 5 steps
This Back to Basics: Getting Started in 5 Steps series will have enlightened you on the fundamental tools used in data science. You will have familiarized yourself with the basics of Python, SQL, machine learning with Scikit-learn and PyTorch, but you will also have ventured into Google Cloud Platform.
The path to data mastery does not end here, it is a continuous journey that requires you to continually learn new skills and the acquired tools to become competent.
Stay tuned to KDnuggets for more information, advanced guides, and support from a community that is as passionate about data science as you are.
nisha arya is a data scientist and freelance technical writer. She is particularly interested in providing professional data science advice or tutorials and theory-based data science insights. She also wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. A great student looking to expand her technological knowledge and writing skills, while she helps guide others.
