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

Guide to Basic Data Types in Python with Examples

Introduction to Python Data Types In this article, we’ll be diving into the Basic Data Types in Python. These form some of the fundamental ways you can represent data. One way to categorize these basic data types is in one of four groups: Numeric: int, float and the less frequently encountered complex Sequence: str (string), list and tuple Boolean: (True or False) Dictionary: dict(dictionary) data type, consisting of (key, value) pairs It’s important to point out that Python usually doesn’t […]

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 Python

Integrating H2 with Python and Flask

Introduction H2 is a lightweight database server written in Java. It can be embedded in Java applications, or run as a standalone server. In this tutorial, we’ll review why H2 can be a good option for your projects. We’ll also learn how to integrate H2 with Python by building a simple Flask API. The Features of H2 H2 was built with performance in mind. “H2 is a combination of: fast, stable, easy to use, and features”. Although H2 is prominent […]

September 25, 2020 Data

Python Data Tools

Python is an increasingly popular object-oriented, interpreted and interactive programming language used for heavy-duty data analysis. Python is designed for ease-of-use, speed, readability and tailored for data-intensive applications. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming styles. It features a fully dynamic type system and automatic memory management, similar to that of Scheme, Ruby, Perl and Tcl. You can create customized data tools using Python that can handle large data sets efficiently – it lets you work more quickly and […]

September 25, 2020 Analysis

An indispensable Python : Data sourcing to Data science.

Data analysis echo system has grown all the way from SQL’s to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run all these operations { Don’t forget the […]

September 25, 2020 Algorithm

Random Forests Algorithm

One of the most popular methods or frameworks used by data scientists at the Rose Data Science Professional Practice Group is Random Forests. The Random Forests algorithm is one of the best among classification algorithms – able to classify large amounts of data with accuracy. Random Forests are an ensemble learning method (also thought of as a form of nearest neighbor predictor) for classification and regression that construct a number of decision trees at training time and outputting the class that is […]

September 25, 2020 Analytics

Python Scikit-learn to simplify Machine learning : { Bag of words } To [ TF-IDF ]

Text (word) analysis and tokenized text modeling always give a chill air around ears, specially when you are new to machine learning. Thanks to Python and its extended libraries for its warm support around text analytics and machine learning. Scikit-learn is a savior and excellent support in text processing when you also understand some of the concept like “Bag of word”, “Clustering” and “vectorization”. Vectorization is must-to-know technique for all machine leaning learners, text miner and algorithm implementor. I personally consider […]

September 25, 2020 Charts

New in Plotly: Interactive Graphs with IPython

New! Plotly lets you style interactive graphs in IPython. Then, you can share your Notebook or your Plotly graph. It’s like having the NYTimes graphics department inside your IPython. You can also get these Notebooks on the Plotly GitHub page. Visit Plot.ly to see more documentation. Here’s a preview of how it looks to have your code, data, and graph all interactively available. See the live version. To finish reading, please visit source site

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