Oct2019 Nov Tutorials, Overviews
All (35) | Courses, Education (1) | Meetings (1) | News (2) | Opinions (5) | Top Stories, Tweets (4) | Tutorials, Overviews (19) | Webcasts & Webinars (3)
- Understanding NLP and Topic Modeling Part 1
- Nov 12, 2019.
In this post, we seek to understand why topic modeling is important and how it helps us as data scientists.
- Research Guide for Depth Estimation with Deep Learning
- Nov 12, 2019.
In this guide, we’ll look at papers aimed at solving the problems of depth estimation using deep learning.
- The Complete Data Science LinkedIn Profile Guide
- Nov 11, 2019.
With so many Data Scientists showing up on LinkedIn, it's time to make sure your profile is top-notch because your talent is still highly sought after. Recruitment specialists want to find you fast, and this guide will help you create the best profile to feature your expertise.
- Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal
- Nov 11, 2019.
ReAgent is a new framework that streamlines the implementation of reasoning systems.
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Understanding Boxplots
- Nov 8, 2019.
A boxplot. It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed. - Orchestrating Dynamic Reports in Python and R with Rmd Files
- Nov 8, 2019.
Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and techniques. Here, we’ll walk through a use-case using both languages in one analysis
- Data Cleaning and Preprocessing for Beginners
- Nov 7, 2019.
Careful preprocessing of data for your machine learning project is crucial. This overview describes the process of data cleaning and dealing with noise and missing data.
- Set Operations Applied to Pandas DataFrames
- Nov 7, 2019.
In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.
- How to Create a Vocabulary for NLP Tasks in Python
- Nov 7, 2019.
This post will walkthrough a Python implementation of a vocabulary class for storing processed text data and related metadata in a manner useful for subsequently performing NLP tasks.
- An Eight-Step Checklist for An Analytics Project
- Nov 6, 2019.
Follow these eight headings of an audit sheet that business analysts should address before submitting the results of their analytics project. One recommended approach is to rewrite each step as a question, answer it, and then attach it to your project.
- Research Guide: Advanced Loss Functions for Machine Learning Models
- Nov 6, 2019.
This guide explores research centered on a variety of advanced loss functions for machine learning models.
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10 Free Must-read Books on AI
- Nov 5, 2019.
Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work. - Probability Learning: Maximum Likelihood
- Nov 5, 2019.
The maths behind Bayes will be better understood if we first cover the theory and maths underlying another fundamental method of probabilistic machine learning: Maximum Likelihood. This post will be dedicated to explaining it.
- Designing Your Neural Networks
- Nov 4, 2019.
Check out this step-by-step walk through of some of the more confusing aspects of neural nets to guide you to making smart decisions about your neural network architecture.
- Customer Segmentation Using K Means Clustering
- Nov 4, 2019.
Customer Segmentation can be a powerful means to identify unsatisfied customer needs. This technique can be used by companies to outperform the competition by developing uniquely appealing products and services.
- Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch
- Nov 4, 2019.
The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.
- Top Machine Learning Software Tools for Developers
- Nov 1, 2019.
As a developer who is excited about leveraging machine learning for faster and more effective development, these software tools are worth trying out.
- Build an Artificial Neural Network From Scratch: Part 1
- Nov 1, 2019.
This article focused on building an Artificial Neural Network using the Numpy Python library.
- What is Machine Learning on Code?
- Nov 1, 2019.
Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.
