Here, you’ll find all intermediate machine learning tutorials. These aim to teach people with some previous knowledge of machine learning concepts and techniques more advanced topics in the field. These tutorials assume that the learner has a basic understanding of machine learning principles, such as supervised and unsupervised learning, and is looking to deepen their knowledge and develop more advanced skills. Intermediate machine learning tutorials cover topics like deep learning, natural language processing and may use more complex datasets and advanced techniques to illustrate the concepts. If you already have some experience with machine learning, intermediate tutorials will be a valuable resource to expand your knowledge of machine learning and improve your skills in the field.
OpenAI and Microsoft have just released a new generation of text-to-speech models that take synthetic speech to a new level. In my latest project I have combined these new models with Azure OpenAI’s ingenuine conversation capacity. The result is a conversational voice bot that uses Generative AI to converse with users in natural spoken language. … Read more
Welcome to the dawn of a new era in digital interaction! With the advent of Generative AI, we’re witnessing a remarkable revolution that’s changing the very nature of how we interact with software and digital services. This change is monumental. Leading the charge are the latest generation of AI-powered virtual assistants, aka “AI copilots”. Unlike … Read more
It’s no secret that Large Language Models (LLMs) are a powerful tool for automating social media tasks. Not only can they be used to curate relevant content that matches your audience’s interests, but also can they create the content and tailor them to the interests of your customers. This article describes how to create a … Read more
Many people use ChatGPT for its text-generation capability and have included it in their day-to-day workflows. However, few people may know that you can use it to create multi-agent conversations between fictional and nonfictional characters. Ever wondered if AI could take you on a time-traveling journey to eavesdrop on a chat between an 18th-century Pirate … Read more
As businesses continue to embrace the power of conversational AI, the ability to craft effective prompts for ChatGPT has become increasingly important. However, this task can be intimidating, particularly when dealing with diverse customer bases and complex industries. But fear not, because this guide is here to help. In this prompt engineering guide, we’ll provide … Read more
Predictive maintenance is a game-changer for the modern industry. Still, it is based on a simple idea: By using machine learning algorithms, businesses can predict equipment failures before they happen. This approach can help businesses improve their operations by reducing the need for reactive, unplanned maintenance and by enabling them to schedule maintenance activities during … Read more
Have you ever wondered how Facebook predicts the future? Meet Facebook Prophet, the open-source time series forecasting tool developed by Facebook’s Core Data Science team. Built on top of the PyStan library, Facebook Prophet offers a simple and intuitive interface for creating forecasts using historical data. What sets Facebook Prophet apart is its highly modular … Read more
Cryptocurrencies like Bitcoin or Ethereum are built on public blockchains, meaning anyone can see the transactions and trades happening on these networks. This transparency makes on-chain data an excellent resource for data science and machine learning. By examining transaction activity and the holdings of Bitcoin addresses, analysts can better understand a cryptocurrency network’s health and … Read more
Content-based recommender systems are a popular type of machine learning algorithm that recommends relevant articles based on what a user has previously consumed or liked. This approach aims to identify items with certain keywords, understand what the customer likes, and then identify other items that are similar to items the user has previously consumed or … Read more
Perfecting your machine learning model’s hyperparameters can often feel like hunting for a proverbial needle in a haystack. But with the Random Search algorithm, this intricate process of hyperparameter tuning can be efficiently automated, saving you valuable time and effort. Hyperparameters are properties intrinsic to your model, like the number of estimators in an ensemble … Read more
Multi-output time series regression can forecast several steps of a time series at once. The number of neurons in the final output layer determines how many steps the model can predict. Models with one output return single-step forecasts. Models with various outputs can return entire series of time steps and thus deliver a more detailed … Read more
