Functional Decomposition and its Utility for Data Scientists & ML Practitioners

Using tools like functional decomposition to enable artificial intelligence, machine learning, and analytics developers in creating better end-to-end solutions

How to: Parse Android Logs for Analytics and Machine Learning Applications

“Where are the logs? I can’t do anything if there aren’t logs!”

Software Engineers most useful tool for debugging is through the analysis of logs. Logs are the ledger that helps keep track of various states of systems at any single time. It is imperative that this historical record be analyzed properly to get the most out of monitoring performance—from complex to simple systems. In this post, Conaxon goes over how to parse Android LogCat Logs for use in analytics and machine learning applications.

ArticlesTyler BetthauserAugust 28, 2021ConaxonLogCat, Android, pandas, parsing, python, os, cwd, log analytics

Keep Analytics, Machine Learning, and Artificial Intelligence to Simple Use-Cases with Collective Vantage

Conaxon takes the reader through a simple sales forecasting project for a retail store. We cover data cleaning (pandas), feature engineering (encoding categorical/cyclical features), building a base GradientBoostedRegressor Model (Sklearn), and hyper-parameter tuning (GridSearchCV, RandomizedSearchCV, KFold).

Be Wary of Second Hand Data: Here's How Collective Vantage Addresses that Fear

A brief discussion how Conaxon & Collective Vantage maintains trust and data quality. You SHOULD be wary of second hand data! But, there are ways to balance the costs and benefits to drive the most value.

Key Struggles with Analytics, Decision Intelligence, and Machine Learning Micro-Business Communities

Conaxon talks about key problems in applying Machine Learning, Artificial Intelligence, Analytics, and Decision Intelligence within Small / Micro Businesses.

Sentiment Analysis to Drive Content Strategy on your YouTube Marketing Channel (Part 2)

Conaxon uses the YouTube API to extract stats and comments from a YouTube channel as a method of using data to drive content strategy that viewers and listeners like watching. Likewise, finding the content that tends to be engaged with more negatively. Deciding content strategy is not an exact science. But, there are tools out there to create a more efficient decision making process. We dive into a few different topics like using APIs, VADER Lexicon from NLTK, for and while loops, cleaning text data, and a dashboard concept to visualize a channel’s data.

Sentiment Analysis to Drive Content Strategy on your YouTube Marketing Channel (Part 1)

Conaxon uses the YouTube API to extract stats and comments from a YouTube channel as a method of using data to drive content strategy that viewers and listeners like watching. Likewise, finding the content that tends to be engaged with more negatively. Deciding content strategy is not an exact science. But, there are tools out there to create a more efficient decision making process. We dive into a few different topics like using APIs, VADER Lexicon from NLTK, for and while loops, cleaning text data, and a dashboard concept to visualize a channel’s data.