Course Description

Optimizer

Jesse E. Agbe

Jesse has been a student of the bible since he got his first bible.He is an avid reader on optimization,productivity,technology.He is a student of ideas,beliefs and philosophies with a desire to see improvement and development in the lives of everyone.His driving goal is to help people to optimize standard technologies in solving certain problems as well as to grow their faith.Jesse loves questions and he is passionate about why things are the way they are and how to be efficient.He is a student,an author and a simple programmer.

Course curriculum

  • 1

    Module 01- Go4DataScience

  • 2

    Module 02 : Go4DataScience - Statistics & Data Analysis

    • Go4DataScience - Statistics with Golang

    • Go4DataScience - Basic Statistics with Gonum

    • Go4DataScience - Exploratory Data Analysis with GoTa

    • Go4DataScience - Source Code For Stats & Data Analysis

    • Go4DataScience - Gonum Crash Course

    • Source Code For Gonum Crash Course
  • 3

    Module 03 - Go4DataScience - Natural Language Processing with Go

    • Go4NLP - Working with Strings, Rune & Byte

    • Go4NLP -Strings Manipulation with Strings Package

    • Go4NLP - Text Cleaning in Regex

    • Go4NLP- Language Detection in Golang

    • Go4NLP - Language Detection with Whatlanggo

    • Go4NLP - Keyword Extraction In Golang

    • Go4NLP - Source Code

    • Go4NLP - Tokenization using Regex

    • Go4NLP - Tokenization using Prose

    • Go4NLP - Parts of Speech Tagging

    • Go4NLP - Creating a Custom Noun Chunker

    • Go4NLP - Creating a Custom Verb Chunker (Exercise)

    • Go4NLP - Entity Chunking with Prose

    • Go4NLP - Named Entity Recognition in Golang with Prose

    • Go4NLP - Natural Language Processing with Prose V2

    • Go4NLP - Text Summarization

    • Go4NLP - Sentiment Analysis using Rule-Based Approach

    • Go4NLP - Sentiment Analysis with a Pretrained Model

    • Go4NLP -Project - Sentiment Analysis (Applying What We Have Learnt)
  • 4

    Go4ML - Machine Learning with Go

    • Go4ML- Introduction & Data Preparation

    • Go4ML-Predicting Hepatitis Status of Blood Donors Using GoML

    • Source Code for Predicting Hepatitis Status of Blood Donors using GoML
  • 5

    Module 05 - Go4DataScience - Web Application Frameworks

    • Go4Web Apps - Introduction

    • Sentiment Analysis Web App -Demo

    • GoFiber - Introduction & Basic App

    • GoFiber - Working with Queries & Params

    • GoFiber- Rendering in HTML

    • GoFiber - Form Handling (Receiving Input From Front-End to BackEnd)

    • GoFiber - Form Handling via POST

    • GoFiber - Working with File Uploads

    • GoFiber - Serving Static Files

    • GoFiber - Showing Uploaded Files In Front-End

    • GoFiber - Working with Bootstrap CSS
  • 6

    Module 05 - Projects

    • Sentiment Analysis Web App - Building the App

    • Sentiment Analysis Web App - Simple API

    • Sentiment Analysis App - Beautifying the App with Bootstrap