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Part II of our adventure to warehouse a subset of DBbSNP's JSON data picks up where Part I left off. Now that we have our database and chromosome 1 file readily available, let's work to stream and parse each line of refsnp-chr1.json.gz, in preparation for database insertion.
In Part II we parsed the JSON data found in the DbSNP JSON download. In Part III, we will bulk-insert this data into our PostgreSQL database.
This series of posts cover how to migrate DbSNPs newly downloadable JSON files into a slimmed-down, relational database containing population frequency data, associated pubmed IDs, and ClinVar data for each SNP in the database.
In this post we introduce Newton’s Method , and how it can be used to solve Logistic Regression . Logistic Regression introduces the concept of the Log-Likelihood of the Bernoulli distribution, and covers a neat transformation called the sigmoid function .
We’ve explored gradient descent , but we haven’t talked about learning rates, and how these hyperparameters are the key differentiators between convergence, and divergence.
In this post I aim to visually, mathematically and programatically explain the gradient , and how its understanding is crucial for gradient descent . For those unfamiliar, gradient descent is used in various ML models spanning from logistic regression, to neural nets. Ultimately, gradient descent, and transitively the gradient , are the blueprints that guide these models to converge on ideal…
Flask-restless is a Flask extension providing generation of REST APIs from SQLAlchemy-defined database models. Flask-restless v1.0.0 introduces adoption of the jsonapi.org spec, providing additional features, consistent and strict HTTP Method contracts, at the expense of inherent breaking changes.
Intro Flask is a versatile microframework capable of doing just about anything that you ask of it. Flask ships with Jinja2 as its HTML Templating Engine, and when combined with SQLAlchemy , provides full-stack development support that rivals bulkier framework (like Django).
This post explains how to connect to SQL Server using SQLAlchemy, pyodbc, UnixODBC and FreeTDS on a Mac
This post shows how to auto-generate a REST API from a handful of SQLAlchemy models. This means full CRUD (POST, GET, PUT, DELETE) endpoint generation for each SQLAlchemy model defined.
Download Oracle instantclient Navigate to the ‘Oracle Instant Client Downloads’ page. Download instantclient-basic-macos.x64-12.1.0.2.0.zip and instantclient-sdk-macos.x64-12.1.0.2.0.zip You will need an Oracle account to proceed with the download. Enter the ‘~/Downloads’ folder in Terminal, and unzip both downloads:
In this post we show how to migrate off of any RDBMS, onto any other RDBMS. We use a case study of Oracle -> MySQL, but we can move between any 2 combinations (SQL Server -> Postgres, MySQL -> SQLite…etc.)