Practices Archives - Liwaiwai

Building Out Your Support Insights Pipeline

Getting into the details We wrote previously about how we used clustering to connect requests for support (in text form) to the best tech support articles so we could answer questions faster and more efficiently. In a constantly changing environment (and in a very oddball couple of years) we wanted to make sure we’re focused on preserving our people’s productivity by isolating, understanding and responding to new support trends as fast as we can. Now we’d like to get into a bit more detail about how we did all that and what went on behind the scenes of our process:…

Debunking 4 Common Myths About Machine Learning

Machine learning is a subset of artificial intelligence that involves the use of algorithms and statistical models to enable computers to improve their performance on a specific task through experience. The experience matters here. It is an increasingly important field with a wide range of applications, from image and speech recognition to natural language processing and decision-making. So, nowadays we can do anything using machine learning as long as we have data available for the job at hand. One of the key advantages of machine learning is its ability to automatically improve and adapt to new data. This allows it…

AI For The Board Game Diplomacy

Agents cooperate better by communicating and negotiating, and sanctioning broken promises helps keep them honest Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial intelligence (AI) research, known for its focus on alliance building. Diplomacy is challenging as it…

Best Practices For Managing Vertex Pipelines Code

Organizations are increasingly using machine learning pipelines to streamline and scale their ML workflows. However, managing these pipelines can be challenging when an organization has multiple ML projects and pipelines at different stages of development. To solve this, we need a way to build upon DevOps concepts and apply them to this ML-specific problem. In this post, we’ll share some best practices on how to manage the codebase for your ML pipelines. The guidance we’re sharing is based on our work with top Google Cloud customers and partners. We’ll provide a few best practices based on pipeline implementation patterns we’ve…

6 Pitfalls to Avoid When Transitioning To a Data Science Career

Making a career change, no matter how big or small is never an easy feat. However, when you’re moving to a field that requires as much technical knowledge as data science, things can get exponentially more difficult. That’s why proper preparation is essential. But here’s the thing: no matter how well-prepared we are, there will always be obstacles on our path to success. Whether internal or external, these hindrances can make it difficult for us to achieve our goals. And sometimes, they can even deter us from following our dreams. Fortunately, however, the better our understanding of the common pitfalls we’re…

Top 10 Data Scientist Skills to Develop to Get Yourself Hired

In my previous story Data Scientist — 12 Steps From Beginner to Pro I described how to master a profession from scratch. In this article, I will focus on the key skills required to become a Data Scientist. ? Hard Skills ? 1. Mathematical base Knowledge of machine learning techniques is an integral part of the Data Scientist job. Working with machine learning algorithms requires an understanding of the basics of calculus (for example, partial differential equations ), linear algebra, statistics (including Bayesian theory), and probability theory. Knowledge of statistics helps the Data Scientist to critically assess the significance of data. The mathematical…

15 Must-Know Machine Learning Algorithms

Machine learning has experienced monumental growth in recent years. We are aware of what can be achieved with machine learning more than ever. The increasing amount of high quality data and advancement in computation have further accelerated the prevalence of machine learning. There is a wide variety of machine learning algorithms that can be grouped in three main categories: Supervised learning algorithms model the relationship between features (independent variables) and a label (target) given a set of observations. Then the model is used to predict the label of new observations using the features. Depending on the characteristics of target variable, it…

10 Steps To Create A Successful Cloud And AI Strategy

To drive business agility and accelerate IT transformation, an integrated hybrid multicloud and AI strategy is key. IT transformation is the basis of competitive advantage for modern enterprises. Your IT infrastructure determines how quickly you can respond to new market opportunities, how fast you scale, and how well you can serve your customers. As the digital economy continues to rapidly expand and evolve, organizations must be able to match its pace. Cloud computing has proven to be instrumental in powering digital transformation that is crucial to achieving true business agility, and hybrid multicloud—the next generation of cloud—is the most flexible and effective IT…

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