Also: Ain’t No Such a Thing as a Citizen Data Scientist; Building Neural Networks with PyTorch in Google Colab. Originally from KDnuggets https://ift.tt/3jO7d3a source https://365datascience.weebly.com/the-best-data-science-blog-2020/top-stories-oct-26-nov-1-how-to-become-a-data-scientist-a-step-by-step-guide-perceptilabs-a-gui-and-visual-api-for-tensorflow
Author Archives: 365Data Science
10 Principles of Practical Statistical Reasoning
Practical Statistical Reasoning is a term that covers the nature and objective of applied statistics/data science, principles common to all applications, and practical steps/questions for better conclusions. The following principles have helped me become more efficient with my analyses and clearer in my conclusions. Originally from KDnuggets https://ift.tt/2I4LlmL source https://365datascience.weebly.com/the-best-data-science-blog-2020/10-principles-of-practical-statistical-reasoning
Healthcare tweet Extraction Visualisation and Particle Swarm Optimisation using Python
Swarm is a large number of agents interacting locally with themselves. In Swarm there’s no supervisor or central control to give orders of… Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/healthcare-tweet-extraction-visualisation-and-particle-swarm-optimisation-using-python-117acc5da470?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/healthcare-tweet-extraction-visualisation-and-particle-swarm-optimisation-using-python
Complete Guide to Numpy for BeginnersPart 3
Complete Guide to Numpy for Beginners — Part 3 This is my 3rd and final blog post on NumPy in which I will be discussing operations, joining, splitting, and filtering of arrays and also about different math functions available in NumPy. If you haven’t checked out my first 2 blog posts on Numpy discussing initializing a NumPy array, indexing,Continue reading “Complete Guide to Numpy for BeginnersPart 3”
130 Machine Learning Projects Solved and Explained
Machine Learning Projects solved and explained for free Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/130-machine-learning-projects-solved-and-explained-897638335f1a?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/130-machine-learning-projects-solved-and-explained
When good data analyses fail to deliver the results you expect
To all those Data Scientists out there who thrive on discovering actionable insights from your data (all of you, right?), take heed from this cautionary tale of a data analysis, a dashboard, and a huge waste of resources. Originally from KDnuggets https://ift.tt/34Qu5uG source https://365datascience.weebly.com/the-best-data-science-blog-2020/when-good-data-analyses-fail-to-deliver-the-results-you-expect
Topic Modeling with BERT
Leveraging BERT and TF-IDF to create easily interpretable topics. Originally from KDnuggets https://ift.tt/3jWB3lY source https://365datascience.weebly.com/the-best-data-science-blog-2020/topic-modeling-with-bert
Data scientist or machine learning engineer? Which is a better career option?
In order to build automated data processing systems, we require professionals like Machine Learning Engineers and Data Scientists. But which of these is a better career option right now? Read on to find out. Originally from KDnuggets https://ift.tt/386k92i source https://365datascience.weebly.com/the-best-data-science-blog-2020/data-scientist-or-machine-learning-engineer-which-is-a-better-career-option
Microsoft and Google Open Sourced These Frameworks Based on Their Work Scaling Deep Learning Training
Google and Microsoft have recently released new frameworks for distributed deep learning training. Originally from KDnuggets https://ift.tt/2Gm7VqL source https://365datascience.weebly.com/the-best-data-science-blog-2020/microsoft-and-google-open-sourced-these-frameworks-based-on-their-work-scaling-deep-learning-training
Beginners Guide -CNN Image Classifier | Part 1
Src: Machine Learning Department, Carnegie Mellon University Step by step guide to building a Deep Neural Network that classifies Images of Dogs and Cats. Content Structure Part 1:1. Problem definition and Goals2. Brief introduction to Concepts & Terminologies3. Building a CNN ModelPart 2:4. Training and Validation5. Image Augmentation6. Predicting Test images7. Visualizing intermediate CNN layers Problem DefinitionContinue reading “Beginners Guide -CNN Image Classifier | Part 1”
