Practical Statistics for Data Scientists – Exploratory Data Analysis
This is an overview of Chapter 1 of Practical Statistics for Data Scientists. Shashank Kalanithi goes over the first couple of chapters of this book because the later chapters cover similar materials from my Hands on Machine Learning book overview videos.
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Top 10 Tools a Data Scientist should Know about in 2021
The work of a data scientist is never done. The work of crafting top 10 lists for data scientist is also never done. Top 10 tools a data scientist should use in 2021 The work of a data scientist centers around the process of extraction of meaningful data from unstructured information and analyzing that data […]
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How is Data Science Affecting Mental Healthcare
The following is a guest post by Ainsley Lawrence, a freelance writer from the Pacific Northwest. She is interested in topics related to better living through education and technology. She is frequently lost in a good book. It likely hasn’t escaped your notice just how much our contemporary society relies on data. From a business […]
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Data Analytics Crash Course: Teach Yourself in 30 Days
freeCodeCamp.org has provided this introduction to Python-based data analytics. You will get a basic understanding of the workings of Python to the point where you can confidently find and manipulate data sources and use a Jupyter environment to derive insights from your data.
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Support Vector Machine Tutorial For Beginners
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Frank
- June 5, 2021
- cancer dataset
- character recognition using support vector machine
- character recognition using SVM in python
- classification algorithms
- classification in machine learning
- edureka
- how does SVM work?
- linear kernel
- Machine Learning
- polynomial kernel
- sci-kit learn
- Support Vector Machine
- Support vector machine implementation
- support vector machine use cases
- Support Vector Machine using python
- SVM
- SVM algorithm
- SVM kernels
- SVM using sci-kit learn
In this tutorial, edureka! explains the Support Vector Machine algorithm.
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SQL For Data Science Tutorial
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Frank
- April 29, 2021
- Data Science
- Data Science Course
- data science edureka
- data science using sql
- database for data science
- edureka
- learn sql
- learn sql database for data science
- learn sql for data science
- mySQL
- mysql commands
- sql and data science
- sql basics for data science
- sql commands
- sql data science tutorial
- sql database in data science
- sql edureka
- sql for beginners
- sql for data science
- sql in data science
- sql tutorial
- What is Data Science
- what is mysql
SQL is a fundamental language of data science, right up there with R and Python, although most people tend not to think of SQL as a language. edureka! provides this basic refresher on SQL for data scientists.
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MLflow Integration with PyCaret and PyTorch
In this talk, hosted by Databricks, learn how to build reproducible AI models and workflows using PyTorch and MLflow that can be shared across your teams, with traceability and speed up collaboration for AI projects.
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How to Parameterize Notebooks for Automation in Azure Data Studio
Jupyter Notebooks bring a wonderful capability to hand someone a single file that contains both code, and instructions on how to run that code. What happens when you need to do the same thing as one of your existing Notebooks, but now you need to do it at scale? What if you could take your […]
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Making Data Science Notebooks Collaborative
Jupyter notebook is now one of the most popular tools for data scientists, even though it is fairly difficult to work with it in a team setting. In this talk, explore how notebooks work under the hood and how we can build collaboration features to enable real-time editing.
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How to Transition to Data Science from a Non Technical Background
Codebasics recently hosted this live stream is to provide career guidance to those who wants to transition to data science or programming career from non technical background.
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