Category Archives: Data Science News

Pipelining the architecture : Image from original paper by authors The raw speech is passed through a feature encoder (temporal CNN blocks + layer norm + GeLU activation) and the latent features are extracted. The latent features are continuous and we need to discretize them for learning speech representations so these features are quantized using some codeContinue reading “Wav2Vec 2.0: Learning Speech Representations via Self-Supervised Objective”

If you are considering starting a career path in machine learning and data science, then there is a great deal to learn theoretically, along with gaining practical skills in applying a broad range of techniques. This comprehensive learning plan will guide you to start on this path, and it is all available for free. OriginallyContinue reading “Learn Data Science for free in 2021”

Model monitoring using a model metric stack is essential to put a feedback loop from a deployed ML model back to model building so that ML models can constantly improve itself under different scenarios. Originally from KDnuggets https://ift.tt/3nqsu4U source https://365datascience.weebly.com/the-best-data-science-blog-2020/mlops-model-monitoring-101

The first issue in 2021 brings you a great blog about Monte Carlo Integration – in Python; An overview of main Machine Learning algorithms you need to know in 2021; SQL vs NoSQL: 7 Key Takeaways; Generating Beautiful Neural Network Visualizations – how to; MuZero – may be the most important Machine Learning system everContinue reading “KDnuggets News 21:n01 Jan 6: All machine learning algorithms you should know in 2021; Monte Carlo integration in Python; MuZero the most important ML system ever created?”

Marketing data science – data science related to marketing – is now a significant part of marketing. Some of it directly competes with traditional marketing research and many marketing researchers may wonder what the future holds in store for it. Originally from KDnuggets https://ift.tt/3ogrD84 source https://365datascience.weebly.com/the-best-data-science-blog-2020/where-is-marketing-data-science-headed

In computer vision world, objects can be viewed through images. And classifying, tagging, segmenting and annotating these are images are important to make the objects of interest perceivable to machines. And in AI world, computer vision is playing big role helping the models understand the scenario around the world making AI possible through machine learningContinue reading “Why Image Segmentation is Needed: Image Segmentation Techniques”

Docking Proteins to Deny Disease: Computational Considerations for Simulating Protein-Ligand Interaction Molecular Docking for Drug Discovery Molecular docking is a powerful tool for studying biological macromolecules and their binding partners. This amounts to a complex and varied field of study, but of particular interest to the drug discovery industry is the computational study of interactionsContinue reading “Docking Proteins to Deny Disease: Computational Considerations for Simulating Protein-Ligand”

Unhidden Organizational Debt of Machine Learning Teams — part 1 image source: wallhere.com The Lord Governor rose from his seat and gazed around the packed arena with pride. “Unleash the Datum Sorcerers!” he thundered, raising his arms skywards. The spectators in their thousands roared in response. The Warlord standing at one side of the governor turned towards him andContinue reading “Unhidden Organizational Debt of Machine Learning Teamspart 1”

Data engineering skills are currently in high demand. If you are looking for career prospects in this fast-growing profession, then these 10 skills and key factors will help you prepare to land an entry-level position in this field. Originally from KDnuggets https://ift.tt/3bgYCpb source https://365datascience.weebly.com/the-best-data-science-blog-2020/how-to-get-a-job-as-a-data-engineer

This post covers how StreamSets can help expedite operations at some of the most crucial stages of Machine Learning Lifecycle and MLOps, and demonstrates integration with Databricks and MLflow. Originally from KDnuggets https://ift.tt/3b9deGU source https://365datascience.weebly.com/the-best-data-science-blog-2020/model-experiments-tracking-and-registration-using-mlflow-on-databricks