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6 key data terms you should know
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Get started in Data Science with Microsoft's FREE course for beginners.

- 10 weeks
- 20 lessons
- Lecture notes
- 100% FREE

https://microsoft.github.io/Data-Science-For-Beginners/
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Essential Charts for Data Analysis
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21 most important equations in data science
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R for Data Science
A
weekly data project aimed at the R ecosystem. As this project was borne out of the R4DS Online Learning Community and the R for Data Science textbook, an emphasis was placed on understanding how to summarize and arrange data to make meaningful charts with ggplot2, tidyr, dplyr, and other tools in the tidyverse ecosystem. However, any code-based methodology is welcome - just please remember to share the code used to generate the results.

Creator: rfordatascience
Stars ⭐️: 5.6k
Forked By: 2.3k
https://github.com/rfordatascience/tidytuesday

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Data Science Components
Data Science for Engineers, IIT Madras

πŸ†“ Free Online Course
πŸ’» 50 Lecture Videos
⏰ 8 Module
πŸƒβ€β™‚οΈ Self paced
Teacher πŸ‘¨β€πŸ« : Prof. Shankar Narasimhan, Prof. Ragunathan Rengasamy

πŸ”— https://nptel.ac.in/courses/106106179

#Data_Science #IIT
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Data science skills matrix
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Why choose data science
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100 Days of Data Science Challenge
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Big and Sparse Data Sciences Integration with Theory, Experiment, Simulations, and Uncertainty Quantification
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book.pdf
2.4 MB
Foundations of Data Science

by Avrim Blum, John Hopcroft, and Ravindran Kannan


πŸ“„ 479 pages


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Your Guide to Latent Dirichlet Allocation

Latent Dirichlet Allocation (LDA) is a β€œgenerative probabilistic model” of a collection of composites made up of parts. Its uses include Natural Language Processing (NLP) and topic modelling, among others.

In terms of topic modelling, the composites are documents and the parts are words and/or phrases (phrases n words in length are referred to as n-grams).

But you could apply LDA to DNA and nucleotides, pizzas and toppings, molecules and atoms, employees and skills, or keyboards and crumbs.

The probabilistic topic model estimated by LDA consists of two tables (matrices). The first table describes the probability or chance of selecting a particular part when sampling a particular topic (category).

Link

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MIT 6.S191: Introduction to Deep Learning 2021
Created by MIT
⏰ 29 hours worth of material
🎬 43 Video lessons
πŸ‘¨β€πŸ« Teacher: Alexander Amini
πŸ”— Course link

#deeplearning #ai #MIT
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Amazon Data Scientist Interview Process
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Data Science Ethics (Login Required)

Utilize the framework provided in the course to analyze concerns related to data science ethics.
Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency.
Examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems.
Learn best practices for responsible data management.
Gain an understanding of the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."

🎬 video lessons
Rating⭐️: 4.1 out 5
πŸƒβ€β™‚οΈ Self paced
Source: University of Michigan

πŸ”— Course Link

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Introduction to the Data Science Process
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deep learning notes.pdf
19.1 MB
Deep Learning Notes
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Data Science vs AI vs ML
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Accelerating Deep Learning with GPUs (Login Required)

Training complex deep learning models with large datasets takes along time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning.
You can use accelerated hardware such as Google’s Tensor Processing Unit (TPU) or Nvidia GPU to accelerate your convolutional neural network computations time on the Cloud. These chips are specifically designed to support the training of neural networks, as well as the use of trained networks (inference). Accelerated hardware has recently been proven to significantly reduce training time.

πŸ†“ Free Online Course
Rating⭐️: 4.7 out 5
🎬 video lesson
πŸƒβ€β™‚οΈ Self paced
Duration ⏰: More than 7 hours worth of material
Source: cognitiveclass
πŸ”— Course Link


#deep_Learning
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2025/09/15 16:59:33
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