• October 2019 (2)
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• March 2019 (10)

Post by Post:

• Markov Chains: How to Train Text Generation to Write like George R. R. Martin
• How to Code MapReduce in C from Scratch Using Threads: Map
• Why do Neural Networks Need an Activation Function?
• LSTM: How to Train Neural Networks to Write like Lovecraft
• 5 Probability Distributions Every Data Scientist Should Know
• Convolutional Neural Networks: Training an Image Classifier with Keras
• K Means Clustering with Dask (Image Filters for Cat Pictures)
• My First 1000 Medium Followers: A Tech Writing Journey
• 3 Machine Learning Books that Helped me Level Up as a Data Scientist
• Autoencoders: Deep Learning with TensorFlow’s Eager Execution
• FuzzyWuzzy: How to Measure String Distance on Python
• XGBoost: Predicting Life Expectancy with Supervised Learning
• Magic: The Gathering Statistics: Clustering the Meta
• K-Means Clustering: Unsupervised Learning for Recommender Systems
• Statistical Analysis: Pandas and Seaborn on a Kaggle Dataset
• Exploratory Data Analysis: Pandas Framework on a Real Dataset
• Vim: How to Start Using The Text Editor for Developers
• Command Magicks: How to Manipulate Files and Strings from the Terminal
• How to Start Using the Terminal to Be More Productive
• How to Scrape the Web using Python with ScraPy Spiders
• How to Run Parallel Data Analysis in Python using Dask Dataframes
• Exploratory Data Analysis with the Pandas Framework and Jupyter Notebooks
• Python’s List Comprehensions: Uses and Advantages
• Vim: Squeezing the Text Editor’s Juice with More Features