Neural Networks vs Deep Learning: What Is the Difference?
Neural networks vs deep learning: what separates them, what each one needs in data and maintenance, and how to pick the right approach for your business.
Author
Bartosz Chojnacki
AI Practice Lead
Bartosz Chojnacki is a seasoned professional in the field of Data Science and Artificial Intelligence, with a robust track record of delivering innovative solutions in the tech industry. With a passion for leveraging big data to drive business strategy and operational efficiency, Bartosz has been at the forefront of integrating AI technologies into practical applications. As a dedicated advocate for the transformative power of AI, Bartosz continues to shape the future of technology through his strategic vision and commitment to excellence.
- 15
Articles
First article
Latest article
Areas of expertise
- Generative AI
- Artificial Intelligence
- Machine Learning
- Data Engineering
- DevOps
Articles by Bartosz Chojnacki
The Great AI Showdown: Why Your Next Business Decision Between Machine Learning and Deep Learning Could Make or Break Your ROI
Discover, based on real-world experimental data, when to choose traditional Machine Learning over Deep Learning for better speed, efficiency, and ROI.
Why Your Next AI Project Might Need Machine Learning Instead of Deep Learning
Read to discover when machine learning outperforms deep learning—and how to choose the right AI approach for your next project.
Generative AI vs Predictive AI: A Guide for Technology Leaders
IT leaders often mix up the two. Generative AI vs predictive AI: how they differ and how to choose the right approach for the business problem you face.
Best No-Code AI Platforms for Building AI Apps in 2025
No-code AI platforms let you build AI apps without writing a line of code. Compare the best tools of 2025 for speed, cost, and results before you commit.
DataRobot vs H2O.ai vs Google AutoML Compared
DataRobot vs H2O.ai vs Google AutoML: compare features, pricing, and performance to choose the best AI and data analytics platform for your team.
Prompt Secrets: AI Agents and Code
Ten advanced prompt engineering techniques for AI agents that write code, from recursive self-improvement to multi-agent collaboration and domain tuning.
The Grand Tour of NLP: spaCy vs. NLTK
spaCy vs NLTK for NLP: compare speed, features, and ease of use to choose the right Python library for your natural language processing project.
Beyond Text Generation: Unpacking the Power of AI Agents vs. Pure LLMs
LLMs generate text, while AI agents act on it. How agents differ from pure LLMs and what that shift means for building more autonomous AI solutions.
Applications of GenAI Agents in Automating Programming Processes
How GenAI agents automate programming work, from code generation to workflow automation, and where they help engineering teams reduce development costs.
Generative AI: Five Predictions for 2024
Five generative AI predictions for 2024, from customized multimodal chatbots and healthcare uses to open-source models, industry adoption, and regulation.
How to Design an Effective GenAI Agent: Best Practices and Challenges
Design principles for GenAI agents in retail: how GPT models and conversational AI make shopping more accessible, plus common development challenges.
Integrating GenAI Agents with Popular Project and Code Management Tools
GenAI agents can automate routine work in project and code management tools. How to integrate them, what they predict, and how they help teams collaborate.
The Business Edge: Leveraging Generative AI on Vertex AI for Competitive Advantage
Generative AI on Vertex AI helps companies personalize customer experiences, automate content and build new products on Google Cloud. Use cases inside.
The Ultimate Guide to Selecting the Right Large Language Model for
How to choose a large language model for your business: compare GPT, Gemini, LLaMa and Mistral on deployment, cost, customization and security.