Data science is a trend that’s not going away anytime soon. It’s been building steadily for years, gaining depth and momentum as advances in technology give us more and more data points to analyse and better tools to analyse them with.
One of those technological game-changers is machine learning. Developments in this field have souped up data science, making it more powerful than ever before – and it’s only getting stronger, with new tools coming out, each more powerful than the last.
Whether you work with or are part of a data team, here are some of the buzzwords you’re going to be hearing a lot of in 2024.
- Automated Machine Learning
Tools: Google AutoML; H20.ai
Imagine a scenario where creating complex machine learning models becomes as intuitive as a few clicks. Automated machine learning (AutoML), epitomised by tools like Google’s AutoML and H2O.ai, is doing just that. By automating this traditionally intricate process, it empowers data scientists to focus on refining models for specific business needs rather than drowning in the complexity of coding. What this means: faster turnaround times and more cost-effective analytics.
- Explainable AI
Tools: LIME; SHAP
Picture an artificial intelligence system making critical decisions in healthcare or finance. With explainable AI (XAI) tools like LIME and SHAP, we’re lifting the veil on AI, providing insights that you don’t need a degree in data science to interpret. For instance, in medical diagnoses, XAI ensures doctors comprehend how an AI model arrived at a particular recommendation. This will translate to more trust in the models and more informed decision-making – which means greater uptake. So, we could see AI moving into areas where it was previously avoided, speeding up and streamlining processes.
- Edge Computing
Tools: TensorFlow Lite; ONNX
Visualise your smart home devices making instant decisions locally, without waiting for a distant server’s response. Edge computing, exemplified by TensorFlow Lite and ONNX, is making this happen by enabling machine learning models to operate closer to the data source. This is not just about speed – it’s about enabling real-time processing for functionality that makes life easier, like facial recognition at your doorstep through the doorbell cam.
- Federated Learning
Tools: Google TensorFlow Federated; PySyft
Concerned about privacy in the digital era? Federated learning is the answer. Consider a scenario where your health data contributes to medical research without leaving your device. Google’s TensorFlow Federated and PySyft are pioneers, ensuring that machine learning models are trained collaboratively across decentralised devices while keeping your sensitive data secure. Essentially, it’s delivering the benefit of having your data used to help advance science without the risk of having it out there on the interwebs where it could fall into the wrong hands.
- Fairness Indicators
Tool: TensorFlow Fairness Indicators
Ethical considerations in AI are not just a buzzword; they’re crucial for societal trust. TensorFlow’s Fairness Indicators is a tool that evaluates and mitigates biases in machine learning models. Think about an AI model used in hiring processes – with fairness indicators, it ensures that biases don’t perpetuate, contributing to a more equitable job market.
- Quantum Machine Learning
Tools: IBM Qiskit; Microsoft Quantum Development Kit
Visualise a future where machine learning models solve problems considered impossible today. The convergence of quantum computing and machine learning, highlighted by IBM’s Qiskit and Microsoft’s Quantum Development Kit, is at the forefront. Quantum machine learning is not just an upgrade; it’s an entirely new realm. More powerful computing capability means more complex problem-solving becomes possible, giving us the freedom to ask questions that we would not have been able to answer previously – and in turn, opening up new possibilities.
Navigating the landscape of data science is not just a professional strategy; it’s the heart of innovation. And these trends are not abstract concepts – they are the building blocks of a future where technology empowers us all.
