September 25, 2020 Python

Statistical Hypothesis Analysis in Python with ANOVAs, Chi-Square, and Pearson Correlation

Introduction Python is an incredibly versatile language, useful for a wide variety of tasks in a wide range of disciplines. One such discipline is statistical analysis on datasets, and along with SPSS, Python is one of the most common tools for statistics. Python’s user-friendly and intuitive nature makes running statistical tests and implementing analytical techniques easy, especially through the use of the statsmodels library. Introducing The statsmodels Library In Python The statsmodels library is a module for Python that gives […]

September 25, 2020 Python

What’s New in Tensorflow 2.0?

Introduction If you are a Machine Learning Engineer, Data Scientist, or a hobbyist developing Machine Learning Models from time to time just for fun, then it is very likely that you are familiar with Tensorflow. Tensorflow is an open-source and a free framework developed by Google Brain Team written in Python, C++, and CUDA. It is used to develop, test, and deploy Machine Learning models. Initially, Tensoflow did not have full support for multiple platforms and programming languages, and it […]

September 25, 2020 Python

Deep Learning Models in Keras – Exploratory Data Analysis (EDA)

Introduction Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications. In many of these applications, deep learning algorithms performed equal to human experts and sometimes surpassed them. Python has become the go-to language for Machine Learning and many of the most popular and powerful deep learning libraries […]

September 25, 2020 Python

Deep Learning in Keras – Data Preprocessing

September 25, 2020 Autoencoder

Open Source Deep Learning Frameworks and Visual Analytics

Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist. What is Deep Learning and Artificial Neural Networks? Deep Learning is the modern buzzword for artificial neural networks, one of many concepts and algorithms in machine learning […]

September 25, 2020 Classifiers

How to automatically create Base Line Estimators using scikit learn.

For any machine learning problem, say a classifier in this case, it’s always handy to create quickly a base line classifier against which we can compare our new models. You don’t want to spend a lot of time creating these base line classifiers; you would rather spend that time in building and validating new features for your final model. In this post we will see how we can rapidly create base line classifier using scikit learn package for any dataset. […]

September 25, 2020 Java

Four great machine learning eBooks

Want to learn machine learning? Looking for data science tutorials and guides to help you master your data and produce actionable, game-changing insights? Look no further than this list of machine learning eBooks from the Packt team…. 1. Python Machine Learning Python Machine Learning is today one of the most popular machine learning titles on the market. And it’s not hard to see why – by bridging the gap between theory and practice, the author Sebastian Raschka provides you with an […]

September 25, 2020 CNN

CNN for Short-Term Stocks Prediction using Tensorflow

In machine learning, a convolutional neural network (CNN, or ConvNet) is a class of neural networks that has successfully been applied to image recognition and analysis. In this project I’ve approached this class of models trying to apply it to stock market prediction, combining stock prices with sentiment analysis. The implementation of the network has been made using TensorFlow, starting from the online tutorial. In this article, I will describe the following steps: dataset creation, CNN training and evaluation of […]

September 25, 2020 Data Science

How to Execute R and Python in SQL Server with Machine Learning Services

Introduction Did you know that you can write R and Python code within your T-SQL statements? Machine Learning Services in SQLServer eliminates the need for data movement. Instead of transferring large and sensitive data over the network or losing accuracy with sample csv files, you can have your R/Python code execute within your database. Easily deploy your R/Python code with SQL stored procedures making them accessible in your ETL processes or to any application. Train and store machine learning models […]

September 21, 2020 Python Leave a comment

The Best Machine Learning Libraries in Python

Introduction There is no doubt that neural networks, and machine learning in general, has been one of the hottest topics in tech the past few years or so. It’s easy to see why with all of the really interesting use-cases they solve, like voice recognition, image recognition, or even music composition. So, for this article I decided to compile a list of some of the best Python machine learning libraries and posted them below. In my opinion, Python is one […]

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