Archives for June 2019

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Fine-tuning with Keras and Deep Learning pyimagesearch.com

Published June 10, 2019 under Machine Learning

In this tutorial, you will learn how to perform fine-tuning with Keras and Deep Learning.

We will take a CNN pre-trained on the ImageNet dataset and fine-tune it to perform image classification and recognize classes it was never trained on.

Today is the final post in our three-part series on fine-tuning:

Part #1: Transfer learning with Keras and Deep Learning
Part #2: Feature extraction with on large datasets with Keras and Deep Learning
Part #3: Fine-tuning with Keras and Deep Learning (today’s post)

CNNs, Part 2: Training a Convolutional Neural Network victorzhou.com

Published June 10, 2019 under Machine Learning

In this post, we’re going to do a deep-dive on something most introductions to Convolutional Neural Networks (CNNs) lack: how to train a CNN, including deriving gradients, implementing backprop from scratch (using only numpy), and ultimately building a full training pipeline!

A high-level app and dashboarding solution for Python pyviz.org

Published June 10, 2019 under Data Science

Panel is an open-source Python library that lets you create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.

How to make the most amount of money with the least amount of risk? towardsdatascience.com

Published June 3, 2019 under Quant Finance

In this article, we show one such amazing application of LP using Python programming in the area of economic planning — maximizing the expected profit from a stock market investment portfolio while minimizing the risk associated with it.

Image Recognition in Python with TensorFlow and Keras

Published June 3, 2019 under Machine Learning

One of the most common utilizations of TensorFlow and Keras is the recognition/classification of images. If you want to learn how to use Keras to classify or recognize images, this article will teach you how.

Text Analysis in Python to Test a Hypothesis dataquest.io

Published June 3, 2019 under Machine Learning

People often complain about important subjects being covered too little in the news. One such subject is climate change. The scientific consensus is that this is an important problem, and it stands to reason that the more people are aware of it, the better our chances may be of solving it. But how can we assess how widely covered climate change is by various media outlets? We can use Python to do some text analysis!

How We Built a Content-Based Filtering Recommender System For Music with Python towardsdatascience.com

Published June 3, 2019 under Data Science

This project refers to Lambda Labs at Lambda School in which students spent the past 5 weeks building production-grade web applications, with some of them utilizing machine learning models as part of their backends.

Data science best practices with pandas dataschool.io

Published June 3, 2019 under Data Science

The pandas library is a powerful tool for multiple phases of the data science workflow, including data cleaning, visualization, and exploratory data analysis. However, the size and complexity of the pandas library makes it challenging to discover the best way to accomplish any given task.