Convolutional Layer in Depth Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/layers-of-convolutional-neural-networks-9fadc0e9acf2?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/layers-of-convolutional-neural-networks
Category Archives: Data Science News
TabPy: Combining Python and Tableau
This article demonstrates how to get started using Python in Tableau. Originally from KDnuggets https://ift.tt/2UUT89V source https://365datascience.weebly.com/the-best-data-science-blog-2020/tabpy-combining-python-and-tableau
Fraud through the eyes of a machine
Data structured as a network of relationships can be modeled as a graph, which can then help extract insights into the data through machine learning and rule-based approaches. While these graph representations provide a natural interface to transactional data for humans to appreciate, caution and context must be applied when leveraging machine-based interpretations of theseContinue reading “Fraud through the eyes of a machine”
How Data Professionals Can Add More Variation to Their Resumes
This article presents seven ways data professionals can add variation to their resumes. Originally from KDnuggets https://ift.tt/3m2Erh0 source https://365datascience.weebly.com/the-best-data-science-blog-2020/how-data-professionals-can-add-more-variation-to-their-resumes
How to Become a CTO?
Not sure what is required for a CTO position? This state of confusion is common in the tech industry due to a lack of detailed and up-to-date information. So, to address this, we reverse-engineered the job descriptions provided by employers for the CTO position to find out the key patterns and skills you need forContinue reading “How to Become a CTO?”
Top Stories Nov 16-22: How to Get Into Data Science Without a Degree
Also: Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision; Facebook Open Sourced New Frameworks to Advance Deep Learning Research; 5 Most Useful Machine Learning Tools every lazy full-stack data scientist should use; Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision; Is Data Science for Me? 14 Self-examinationContinue reading “Top Stories Nov 16-22: How to Get Into Data Science Without a Degree”
15 Exciting AI Project Ideas for Beginners
There are many branches to AI to learn, but a project-based approach can keep things interesting. Here is a list of 15 such projects you can get started on implementing today. Originally from KDnuggets https://ift.tt/3l0dwkJ source https://365datascience.weebly.com/the-best-data-science-blog-2020/15-exciting-ai-project-ideas-for-beginners
Know-How to Learn Machine Learning Algorithms Effectively
The takeaway from the story is that machine learning is way beyond a simple fit and predict methods. The author shares their approach to actually learning these algorithms beyond the surface. Originally from KDnuggets https://ift.tt/373vBt8 source https://365datascience.weebly.com/the-best-data-science-blog-2020/know-how-to-learn-machine-learning-algorithms-effectively
How To Revolutionize Your Digital Workplace With AI
The pandemic crisis has demystified a long-drawn conclusion of work from office holding an edge over remote work. Organizations globally are prioritizing their investments in digital workplace transformation mapping to the work from home or hybrid work environment. Enterprises will need to focus on flexibility and agility in response to adapt to a fast-changing situation.Continue reading “How To Revolutionize Your Digital Workplace With AI”
Convolutional Neural Networks (CNNs / ConvNets) for Visual Recognition
Photo by JJ Ying on Unsplash Convolutional Neural Networks are very similar to ordinary Neural Networks. They are made up of neurons that have learnable weights and biases. Each neuron receives some inputs, performs a dot product, and optionally follows it with a non-linearity. The whole network still expresses a single differentiable score function: from theContinue reading “Convolutional Neural Networks (CNNs / ConvNets) for Visual Recognition”
