ML and Causality – Why?
Machine learning is Competence without Comprehension as famously noted by Dan Dennett, the pre-eminent philosopher of our times. There are two aspects to Machine Learning… Read More »ML and Causality – Why?
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Machine Learning
Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
Seven Rules for Delivering Machine Learning Projects on Time
Predicting the length of time it will take to get a Machine Learning (ML) project into production can be tricky. If there is an issue,… Read More »Seven Rules for Delivering Machine Learning Projects on Time
Model Versioning: Reduce Friction. Create Stability. Automate.
The research and development (R&D) phase of building an AI model to address a business problem is characterized by rapid exploration and iteration. Everything is… Read More »Model Versioning: Reduce Friction. Create Stability. Automate.
Neural Translation – Machine Translation with Neural Nets with Keras / Python
In this blog, we shall discuss about how to build a neural network to translate from English to German. This problem appeared as the Capstone… Read More »Neural Translation – Machine Translation with Neural Nets with Keras / Python
Your Guide for the Commonly Used Machine Learning Algorithms
We are currently living in such a period where computing has transformed immensely from large mainframes to personal computers to the cloud. The constant technological… Read More »Your Guide for the Commonly Used Machine Learning Algorithms
Applications of real-world reinforcement learning
This blog is the second part of a two-blog series. Here, we discuss different sectors where reinforcement learning can be used to solve complex problems… Read More »Applications of real-world reinforcement learning
Honey I Shrunk the Model: Why Big Machine Learning Models Must Go Small
Bigger is not always better for machine learning. Yet, deep learning models and the datasets on which theyre trained keep expanding, as researchers race to… Read More »Honey I Shrunk the Model: Why Big Machine Learning Models Must Go Small
Model Training: Our Favorite Tools in the Shed
Welcome to the second installment of our ModelOps blog series, where we dive deep into the next step in the ModelOps pipeline, Model Training. During… Read More »Model Training: Our Favorite Tools in the Shed
How TensorFlow Works?
Tensor Flow permits the subsequent: Tensor Flow helps you to deploy computation to as a minimum one or extra CPUs or GPUs in a computing… Read More »How TensorFlow Works?
Leveraging SAP’s Enterprise Data Management tools to enable ML/AI success
Background In our previous blog post, Master Your ML/AI Success with Enterprise Data Management, we outlined the need for Enterprise Data Management (EDM) and ML/AI… Read More »Leveraging SAP’s Enterprise Data Management tools to enable ML/AI success