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Destin Gong
Destin Gong

1.8K Followers

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Published in Towards Data Science

·Pinned

An Interactive Guide to Hypothesis Testing in Python

T-Test, ANOVA, Chi-Squared Test with Examples — What is Hypothesis Testing? Hypothesis testing is an essential part in inferential statistics where we use observed data in a sample to draw conclusions about unobserved data — often the population. Implication of hypothesis testing: clinical research: widely used in psychology, biology and healthcare research to examine the effectiveness of clinical trials

Hypothesis Testing

10 min read

An Interactive Guide to Hypothesis Testing in Python
An Interactive Guide to Hypothesis Testing in Python
Hypothesis Testing

10 min read


Published in Towards Data Science

·Pinned

Top 6 Machine Learning Algorithms for Classification

How to Build a Machine Learning Model Pipeline in Python — Supervised vs. Unsupervised vs. Reinforcement Learning The easiest way to distinguish a supervised learning and unsupervised learning is to see whether the data is labelled or not. Supervised learning learns a function to make prediction of a defined label based on the input data. It can be either classifying data into a category (classification problem) or…

Classification Algorithms

9 min read

Top 6 Machine Learning Algorithms for Classification
Top 6 Machine Learning Algorithms for Classification
Classification Algorithms

9 min read


Published in Towards Data Science

·Pinned

How to Self-Learn Data Science in 2022

A Project Based Approach to Get Started in Data Science — As someone who don’t hold a degree in data science, I am truly passionate about this field and decided to experiment on building my own curriculum to learn data science in spare time. I would like to share my experience and hope to bring some insights if you want to…

Data Science Training

7 min read

How to Self-Learn Data Science in 2022
How to Self-Learn Data Science in 2022
Data Science Training

7 min read


Published in Towards Data Science

·Pinned

Semi-Automated Exploratory Data Analysis (EDA) in Python

Comprehensive Data Exploration Process with One-Click — Exploratory Data Analysis, also known as EDA, has become an increasingly hot topic in data science. Just as the name suggests, it is the process of trial and error in an uncertain space, with the goal of finding insights. It usually happens at the early stage of the data science…

Eda

11 min read

Semi-Automated Exploratory Data Analysis (EDA) in Python
Semi-Automated Exploratory Data Analysis (EDA) in Python
Eda

11 min read


Published in Towards Data Science

·Jan 25

A Visual Learner’s Guide to Explain, Implement and Interpret Principal Component Analysis (PCA)

Linear Algebra for Machine Learning — Covariance Matrix, Eigenvector and Principal Component — In my previous article, we have talked about applying linear algebra for data representation in machine learning algorithms, but the application of linear algebra in ML is much broader than that. How is Linear Algebra Applied for Machine Learning? Starting from using matrix and vector for data representationtowardsdatascience.com

Machine Learning

11 min read

A Visual Learner’s Guide to Explain, Implement and Interpret Principal Component Analysis
A Visual Learner’s Guide to Explain, Implement and Interpret Principal Component Analysis
Machine Learning

11 min read


Published in Towards Data Science

·Dec 30, 2022

How is Linear Algebra Applied in Machine Learning

Starting from using matrix and vector for data representation — Truth be told, the role of linear algebra in machine learning has been perplexing me, as mostly we learn these concepts (e.g. vector, matrix) in a math background while discarding their applications in the machine learning context. In fact, linear algebra has several foundational use cases in machine learning, including…

Linear Algebra

9 min read

Linear Algebra for ML | Matrix, Vector and Data Representation
Linear Algebra for ML | Matrix, Vector and Data Representation
Linear Algebra

9 min read


Published in Towards Data Science

·Dec 13, 2022

How to Use Plotly for More Insightful and Interactive Data Explorations

Case Study: Dynamic EDA for Qatar World Cup Teams — This article will introduce the tool, Plotly [1], that brings data visualization and exploratory data analysis (EDA) to the next level. You can use this open source graphing library to make your notebook more aesthetic and interactive, regardless if you are a Python or R user. To install Plotly, use…

Eda

6 min read

How to Use Plotly for More Insightful and Interactive Data Explorations
How to Use Plotly for More Insightful and Interactive Data Explorations
Eda

6 min read


Published in Towards Data Science

·Nov 18, 2022

Time Series Analysis Introduction — A Comparison of ARMA, ARIMA, SARIMA Models

On the differences between these models, and how you should use them — What is Time Series? Time series is a unique type of problem in machine learning where the time component plays a critical role in the model predictions. As observations are dependent on adjacent observations, this violates the assumption that observations are independent to each other followed by most conventional machine learning models. Common use…

Time Series Analysis

12 min read

Time Series Analysis Introduction — A Comparison of ARMA, ARIMA, SARIMA Models
Time Series Analysis Introduction — A Comparison of ARMA, ARIMA, SARIMA Models
Time Series Analysis

12 min read


Published in Dev Genius

·Jun 14, 2022

How to Visualize Twitter Trends in 4 Simple Steps

A Swift Approach to Spot Trending Topics in 10 Minutes — 1. Install Twint and Import Libraries Twint is a powerful yet straightforward Python package that allows scraping Twitter posts. GitHub — twintproject/twint: An advanced Twitter scraping & OSINT tool written in Python that… An advanced Twitter scraping & OSINT tool written in Python that doesn’t use Twitter’s API, allowing you to scrape a…github.com

Python

4 min read

How to Visualize Twitter Trends in 4 Simple Steps
How to Visualize Twitter Trends in 4 Simple Steps
Python

4 min read


Published in Towards Data Science

·Jun 3, 2022

TensorFlow Template for Deep Learning Beginners

How to Build Your First Deep Neural Network — What is Deep Learning? Deep learning is a sub-category of machine learning models that uses neural networks. In a nutshell, neural networks connect multiple layers of nodes and each node can be considered as a mini machine learning model. The output of the model then feeds as the input of the subsequent node.

Deep Learning

7 min read

TensorFlow Template for Deep Learning Beginners
TensorFlow Template for Deep Learning Beginners
Deep Learning

7 min read

Destin Gong

Destin Gong

1.8K Followers

On my way to become a data storyteller | Website: www.visual-design.net

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