# KDnuggets™ News 20:n26, Jul 8: Speed up Your Numpy and Pandas; A Layman’s Guide to Data Science; Getting Started with TensorFlow 2

Speed up your Numpy and Pandas with NumExpr Package; A Layman's Guide to Data Science. Part 3: Data Science Workflow; Getting Started with TensorFlow 2; Feature Engineering in SQL and Python: A Hybrid Approach; Deploy Machine Learning Pipeline on AWS Fargate

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Features

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Tutorials, Overviews

Opinions

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This week: We show how to significantly speed up your mathematical calculations in Numpy and Pandas using a small library; Learn and appreciate the typical workflow for a data science project, including data preparation, analysis, reflection, and communication of the results; Learn about the latest version of TensorFlow with a hands-on walk-through of implementing a classification problem with deep learning; See a hybrid approach to feature engineering in SQL and Python; Read a step-by-step beginner's guide to containerize and deploy ML pipeline serverless on AWS Fargate.

Features

**Speed up your Numpy and Pandas with NumExpr Package****A Layman's Guide to Data Science. Part 3: Data Science Workflow****Getting Started with TensorFlow 2****Feature Engineering in SQL and Python: A Hybrid Approach****Deploy Machine Learning Pipeline on AWS Fargate**

News

**5th International Summer School 2020 on Resource-aware Machine Learning (REAML)****Innovating versus Doing: NLP and CORD19****Lynx Analytics is open-sourcing LynxKite, its Complete Graph Data Science Platform****Five Lines of Code**

Tutorials, Overviews

**Some Things Uber Learned from Running Machine Learning at Scale****A Complete Guide To Survival Analysis In Python, part 1****PyTorch for Deep Learning: The Free eBook****Exploratory Data Analysis on Steroids****Generating cooking recipes using TensorFlow and LSTM Recurrent Neural Network: A step-by-step guide****PyTorch Multi-GPU Metrics Library and More in New PyTorch Lightning Release****Data Cleaning: The secret ingredient to the success of any Data Science Project****Software engineering fundamentals for Data Scientists****How to Prepare Your Data****Learn Data Science from Top Universities for Free****An Introduction to Statistical Learning: The Free eBook****Practical Markov Chain Monte Carlo****Free Economics & Finance Courses for Data Scientists****Build a Branded Web Based GIS Application Using R, Leaflet and Flexdashboard****The 8 Basic Statistics Concepts for Data Science****Time Complexity: How to measure the efficiency of algorithms**

Opinions

**Scope and Impact of AI in Agriculture****Data Scientists Have Developed a Faster Way to Reduce Pollution, Cut Greenhouse Gas Emissions****Largest Dataset Analyzed - Poll Results and Trends****How to Build Your Data Science Competency for Post-COVID Future****Stop training more models, start deploying them****The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP)****How Much Math do you need in Data Science?****Exploring the Real World of Data Science****Data Science Tools Popularity, animated****Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron****Machine Learning Engineer vs Data Scientist (Is Data Science Over?)**

Top Stories, Tweets

**Top Stories, Jun 29 - Jul 5: Speed up your Numpy and Pandas with NumExpr Package; Deploy Machine Learning Pipeline on AWS Fargate****Top Stories, Jun 22-28: How Much Math do you need in Data Science?****Top KDnuggets tweets, Jun 17-23: The Best NLP with Deep Learning Course is Free**

Jobs

- See our recent jobs in AI, Analytics, Data Science, Machine Learning
- You can post a free short entry on KDnuggets jobs page for an industry or academic job related to AI, Big Data, Data Science, or Machine Learning, email - see details at kdnuggets.com/jobs

Image of the week

From A Layman’s Guide to Data Science. Part 3: Data Science Workflow