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Marketing

Best practices for chatbot development

To build an effective AI chatbot for your business, it’s crucial to first understand who your customers are and what problems they face. Engaging potential customers and boosting profitability starts with addressing their pain points.

Marketing

How to handle challenges in artificial intelligence

These simple applications bridge human inquiries with AI-powered responses, showcasing AI's ability to process and respond to basic tasks efficiently.But the AI landscape has rapidly evolved. From AI-generated art to the ChatGPT phenomenon, artificial intelligence is no longer limited to basic functionality. Instead, it’s transitioning from theoretical concepts to real-world applications at a breakneck pace. This shift is turning possibilities into realities, bringing AI’s potential — and its complexities — into sharper focus.

Marketing

Python or Julia for data science: Which one works best?

While Python may not inherently excel in statistical analysis, its straightforward design and ease of use make it a favorite among data scientists. Python’s simplicity allows even beginners to pick it up quickly, and the vast array of free analytical libraries—like NumPy, Pandas, and SciPy—means data scientists can find ready-made tools to handle almost any task with minimal setup.