Multilingual NLI Dataset
Moritz Laurer, a PhD researcher working with NLP at Vrije Univeristy of Amsterdam, announced on his Twitter account that new multilingual dataset is ready!
New dataset contains 2 730 000 NLI text pairs in 26 languages. It was created from previous English dataset using the latest open-source machine translation model.
The dataset can be loaded here.
Moritz Laurer, a PhD researcher working with NLP at Vrije Univeristy of Amsterdam, announced on his Twitter account that new multilingual dataset is ready!
New dataset contains 2 730 000 NLI text pairs in 26 languages. It was created from previous English dataset using the latest open-source machine translation model.
The dataset can be loaded here.
huggingface.co
MoritzLaurer/multilingual-NLI-26lang-2mil7 · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Free Machine Learning Course
Learn ML engineering in 4 months in a free online course by Al_Grigor from DataTalksClub
What you will learn:
- Linear and logistic regression
- Tree-based models
- Neural networks
- Deployment with AWS, Serverless, Kubernetes
Register here: Link
Learn ML engineering in 4 months in a free online course by Al_Grigor from DataTalksClub
What you will learn:
- Linear and logistic regression
- Tree-based models
- Neural networks
- Deployment with AWS, Serverless, Kubernetes
Register here: Link
Understanding The Structure of Your Data
1) Univariate Visualization: This visualization is used to gain a summary statistics of each feature in your dataset. The goal of univariate visualization is to have a solid understanding of the data in order to start querying and visualizing our data in various ways. It uses tools such as barplots and histograms to reveal the structure of the data.
2) Bivariate Visualization: This visualization is used when you need to find relationships between two variables in your dataset where one of the variable could be the target variable. It uses correlations, scatter plots and line plots to reveal structure of the data.
3) Multivariate Visualization: This is employed to understand interactions between different fields in the dataset. It uses line plots, scatter plots, and matrices with multiple colors to understand the relationship between various features of a dataset.
1) Univariate Visualization: This visualization is used to gain a summary statistics of each feature in your dataset. The goal of univariate visualization is to have a solid understanding of the data in order to start querying and visualizing our data in various ways. It uses tools such as barplots and histograms to reveal the structure of the data.
2) Bivariate Visualization: This visualization is used when you need to find relationships between two variables in your dataset where one of the variable could be the target variable. It uses correlations, scatter plots and line plots to reveal structure of the data.
3) Multivariate Visualization: This is employed to understand interactions between different fields in the dataset. It uses line plots, scatter plots, and matrices with multiple colors to understand the relationship between various features of a dataset.
Machine Learning YouTube Courses
This repo contains some of the best and most recent machine learning courses available on YouTube.
Creator: dair-ai
Stars⭐️: 8.1k
Fork: 977
Repo Link: Click Me
This repo contains some of the best and most recent machine learning courses available on YouTube.
Creator: dair-ai
Stars⭐️: 8.1k
Fork: 977
Repo Link: Click Me
FREE UDEMY COURSES
Artificial Neural Networks (ANN) with Keras in Python and R
Rating ⭐️: 4.3 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 153,510
Created by: Star Tech Academy
🔗 Course link
Marketing Analytics: Forecasting Models with Excel
Rating ⭐️: 4.5 out of 5
Duration ⏰: 7 hours on-demand video
Students 👨🏫: 134, 539
Created by: Star Tech Academy
🔗 Course link
Decision Trees, Random Forests, Bagging & XGBoost: R Studio
Rating ⭐️: 4.6 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 60,768
Created by: Star Tech Academy
🔗 Course link
#machine_learning l #datascience #datanalysis #neural_networks #deep_learning #ai #python
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Artificial Neural Networks (ANN) with Keras in Python and R
Rating ⭐️: 4.3 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 153,510
Created by: Star Tech Academy
🔗 Course link
Marketing Analytics: Forecasting Models with Excel
Rating ⭐️: 4.5 out of 5
Duration ⏰: 7 hours on-demand video
Students 👨🏫: 134, 539
Created by: Star Tech Academy
🔗 Course link
Decision Trees, Random Forests, Bagging & XGBoost: R Studio
Rating ⭐️: 4.6 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 60,768
Created by: Star Tech Academy
🔗 Course link
#machine_learning l #datascience #datanalysis #neural_networks #deep_learning #ai #python
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Udemy
Artificial Neural Networks (ANN) with Keras in Python and R
Understand Deep Learning and build Neural Networks using TensorFlow 2.0 and Keras in Python and R
GOOGLE CLOUD FREE MACHINE LEARNING AND AI COURSE
Learn how to implement the latest machine learning and artificial intelligence technology by exploring training on BigQuery, TensorFlow, Cloud Vision, Natural Language API, and more
what you will learn:
👌Big Data & Machine Learning Fundamentals
👌Perform Foundational Data, ML, and AI Tasks in Google Cloud
👌Machine Learning on Google Cloud
👌Advanced Machine Learning with TensorFlow on Google Cloud Platform
👌MLOps (Machine Learning Operations) Fundamentals
👌ML Pipelines on Google Cloud
👌Build and Deploy Machine Learning Solutions on Vertex AI
👌Create Conversational AI Agents with Dialogflow CX
https://cloud.google.com/training/machinelearning-ai
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Learn how to implement the latest machine learning and artificial intelligence technology by exploring training on BigQuery, TensorFlow, Cloud Vision, Natural Language API, and more
what you will learn:
👌Big Data & Machine Learning Fundamentals
👌Perform Foundational Data, ML, and AI Tasks in Google Cloud
👌Machine Learning on Google Cloud
👌Advanced Machine Learning with TensorFlow on Google Cloud Platform
👌MLOps (Machine Learning Operations) Fundamentals
👌ML Pipelines on Google Cloud
👌Build and Deploy Machine Learning Solutions on Vertex AI
👌Create Conversational AI Agents with Dialogflow CX
https://cloud.google.com/training/machinelearning-ai
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*This channel belongs to @bigdataspecialist group
Data Cleaning Checklist
Data cleaning takes up 80% of the data science workflow. Use this checklist to identify and resolve any quality issues with your data.
Link
Data cleaning takes up 80% of the data science workflow. Use this checklist to identify and resolve any quality issues with your data.
Link
I understand data science is not all about programming but, as far as I know, Python comes into play to some extent on this matter. How much should I know about programming to do data science?
This question was asked earlier today by one our community member in our main channel @bigdataspecialist.
I decided to share my answer here since it might be interesting to some of you and I am pretty sure great majority of you haven't even noticed his question/my answer.
TL:DR
Programming is important, but you don't have to be an expert. You just need some basic to intermediate skills to prepare your data (which you are going to use in data science tasks), possibly make some data visualizations to gain insights and at the end to create your machine learning models. These basic skills could probably be gained in a month, especially if you are not complete newbie who has never heard of programming 😅
You can get mentioned skills from this course: https://www.coursera.org/learn/python-data-analysis
Teacher is Christopher Brooks and course is created by University of Michigan.
Note: I know it says its paid one, buy you can apply for financial aid and get course for free. That's how I got this course when I just started learning data science.
Keep in mind that Python is not only programming language which comes to mind when you think about doing data science.
For example, for almost all data science and machine learning tasks, I use Java. It's very specific and usually data scientists don't do that, but platform developed by my company is receiving 4k requests per second, so we need something blazing fast, and Python is pretty slow. That's why we use Java.
But if I am going to test something locally, or I need some easy data preparation or data visualizations, I use Python. Creating charts to gain some insights would be real nightmare with Java. But for you as a beginner Python is probably best choice
Long story short:
If you want it fast and easy, python is way to go
IF you want it very fast (but probably pretty hard to make it work) - Java.
If you want to perform advanced calculations and visualizations - R
If you want to show your visualizations dynamically on some web page, then certain JavaScript libraries like D3.js or chart.js.
Hope this helps.
➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
This question was asked earlier today by one our community member in our main channel @bigdataspecialist.
I decided to share my answer here since it might be interesting to some of you and I am pretty sure great majority of you haven't even noticed his question/my answer.
TL:DR
Programming is important, but you don't have to be an expert. You just need some basic to intermediate skills to prepare your data (which you are going to use in data science tasks), possibly make some data visualizations to gain insights and at the end to create your machine learning models. These basic skills could probably be gained in a month, especially if you are not complete newbie who has never heard of programming 😅
You can get mentioned skills from this course: https://www.coursera.org/learn/python-data-analysis
Teacher is Christopher Brooks and course is created by University of Michigan.
Note: I know it says its paid one, buy you can apply for financial aid and get course for free. That's how I got this course when I just started learning data science.
Keep in mind that Python is not only programming language which comes to mind when you think about doing data science.
For example, for almost all data science and machine learning tasks, I use Java. It's very specific and usually data scientists don't do that, but platform developed by my company is receiving 4k requests per second, so we need something blazing fast, and Python is pretty slow. That's why we use Java.
But if I am going to test something locally, or I need some easy data preparation or data visualizations, I use Python. Creating charts to gain some insights would be real nightmare with Java. But for you as a beginner Python is probably best choice
Long story short:
If you want it fast and easy, python is way to go
IF you want it very fast (but probably pretty hard to make it work) - Java.
If you want to perform advanced calculations and visualizations - R
If you want to show your visualizations dynamically on some web page, then certain JavaScript libraries like D3.js or chart.js.
Hope this helps.
➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
Coursera
Introduction to Data Science in Python
Offered by University of Michigan. This course will ... Enroll for free.
Huge collection of Data Science materials
By Harvard
You will find lecture notes/Notebooks for every data science/machine learning topic you heard about 🤯
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
By Harvard
You will find lecture notes/Notebooks for every data science/machine learning topic you heard about 🤯
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
Understanding and Handling Overfitting
When a machine learning method fits the Training Data really well but makes poor predictions, we say that it is Overfit to the Training Data.
Let's try to undertstand how this occurs and how to handle it,
1) Overfitting in Machine Learning
Link
2) Overfitting and Underfitting With Machine Learning Algorithms
Link
3) Overfitting by IBM
Link
4) The Complete Guide on Overfitting and Underfitting in Machine Learning
Link
When a machine learning method fits the Training Data really well but makes poor predictions, we say that it is Overfit to the Training Data.
Let's try to undertstand how this occurs and how to handle it,
1) Overfitting in Machine Learning
Link
2) Overfitting and Underfitting With Machine Learning Algorithms
Link
3) Overfitting by IBM
Link
4) The Complete Guide on Overfitting and Underfitting in Machine Learning
Link
FREE DATA SCIENCE, MACHINE LEARNING AND DEEP LEARNING COURSES WITH CERTIFICATES
1) Data Science 101
Rating ⭐️: 5.6k+
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Duration ⏰: 3 hours on-demand video
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3) Game-playing AI with Swift for TensorFlow (S4TF)
Rating ⭐️: 20
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1) Data Science 101
Rating ⭐️: 5.6k+
Duration ⏰: 3 hours on-demand video
Course Link : Enroll Now
2) Deep Learning Fundamentals
Rating ⭐️: 5.6k+
Duration ⏰: 3 hours on-demand video
Course Link : Enroll Now
3) Game-playing AI with Swift for TensorFlow (S4TF)
Rating ⭐️: 20
Duration ⏰:4 hours of on-demand video
Course Link: Enroll Now
4) Introduction to Machine Learning with Sound
Rating ⭐️: 17.1k+
Duration ⏰: 4 hours of on-demand video
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TENSORFLOW FREE LEARNING RESOURCES
1) Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
COURSE LINK: Click Me
Source: O reily
2) Intro to TensorFlow for Deep Learning
This course is a practical approach to deep learning for software developers
Course Link: Click Me
Source: Udacity
3) Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Course Link: Click Me
Source: Coursera
4) Get Started With TensorFlow
Course Link: Click Me
Source: TensorFlow
5) Tensorflow | Tensorflow Tutorial For Beginners | Intellipaat
Course Link: Click Me
Source: Intellipaat
6) Practical Machine Learning with Tensorflow
Course is jointly offered by Google and IIT Madras. After this course, the students will be able to build ML models using Tensorflow.
Course Link: Click Me
Source: NPTEL
7) TensorFlow Full Course
Course Link: Click Me
Source: Simplilearn
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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1) Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
COURSE LINK: Click Me
Source: O reily
2) Intro to TensorFlow for Deep Learning
This course is a practical approach to deep learning for software developers
Course Link: Click Me
Source: Udacity
3) Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Course Link: Click Me
Source: Coursera
4) Get Started With TensorFlow
Course Link: Click Me
Source: TensorFlow
5) Tensorflow | Tensorflow Tutorial For Beginners | Intellipaat
Course Link: Click Me
Source: Intellipaat
6) Practical Machine Learning with Tensorflow
Course is jointly offered by Google and IIT Madras. After this course, the students will be able to build ML models using Tensorflow.
Course Link: Click Me
Source: NPTEL
7) TensorFlow Full Course
Course Link: Click Me
Source: Simplilearn
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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O’Reilly Media
Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
Data Analysis with Python: Zero to Pandas
Data Analysis with Python: Zero to Pandas" is a practical and beginner-friendly introduction to data analysis covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis.
The course is self-paced and there are no deadlines. There are no prerequisites for this course.
👌Watch hands-on coding-focused video tutorials
👌Practice coding with cloud Jupyter notebooks
👌Build an end-to-end real-world course project
👌Earn a verified certificate of accomplishment
👌Interact with a global community of learners
Link:https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas
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Data Analysis with Python: Zero to Pandas" is a practical and beginner-friendly introduction to data analysis covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis.
The course is self-paced and there are no deadlines. There are no prerequisites for this course.
👌Watch hands-on coding-focused video tutorials
👌Practice coding with cloud Jupyter notebooks
👌Build an end-to-end real-world course project
👌Earn a verified certificate of accomplishment
👌Interact with a global community of learners
Link:https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas
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jovian.ai
Data Analysis with Python: Zero to Pandas | Jovian
A practical, beginner-friendly, and coding-focused introduction Python, Numpy, Pandas, data visualization, and exploratory data analysis. Earn a verified certificate of accomplishment by completing assignments & building a real-world project.
Learn PyTorch for Deep Learning
Pytorch is a popular framework for doing Machine Learning in Python. You can use it to build data models, then ask questions of those models. If you're interested in Data Science, and know a bit of Python, this course is a solid place to start your journey. You'll code along at home as you learn about Datasets, Neural Networks, Computer Vision, and more.
Course Link
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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*This channel belongs to @bigdataspecialist group
Pytorch is a popular framework for doing Machine Learning in Python. You can use it to build data models, then ask questions of those models. If you're interested in Data Science, and know a bit of Python, this course is a solid place to start your journey. You'll code along at home as you learn about Datasets, Neural Networks, Computer Vision, and more.
Course Link
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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freeCodeCamp.org
Learn PyTorch for Deep Learning – Free 26-Hour Course
By Daniel Bourke My comprehensive PyTorch course is now live on the freeCodeCamp.org YouTube channel. You can view the full 26 hour course here. Read the course materials online for free at learnpytorch.io. See all of the course materials on GitHub...
Practical Statistics for Data Scientist Free Book
Creator: ghoshark
Stars ⭐️: 100
Forked By: 48
GithubRepo: Link
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Creator: ghoshark
Stars ⭐️: 100
Forked By: 48
GithubRepo: Link
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Udacity Data Science Course
Want to learn what it takes to be a data scientist 🤯? Hop on this course😁.
Not to worry, It is beginner friendly😄.
Here's what you will be learning:
😎Data Manipulation
😎Data Analysis with Statistics and Machine Learning
😎Data Communication with Information Visualization
😎Data at Scale -- Working with Big Data
Course Link: Enroll Now👈
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*This channel belongs to @bigdataspecialist group
Want to learn what it takes to be a data scientist 🤯? Hop on this course😁.
Not to worry, It is beginner friendly😄.
Here's what you will be learning:
😎Data Manipulation
😎Data Analysis with Statistics and Machine Learning
😎Data Communication with Information Visualization
😎Data at Scale -- Working with Big Data
Course Link: Enroll Now👈
➖➖➖➖➖➖➖➖➖➖➖➖➖
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*This channel belongs to @bigdataspecialist group
Fast.AI Practical Deep Learning Course!!!
This super amazing😱 free course😍 is designed for people with some coding experience who want to learn how to apply deep learning and machine learning to practical problems🤩.
Here's what you will be learning from this course😉:
😇Build and train deep learning models for computer vision, natural language processing, tabular analysis, and collaborative filtering problems
😇Create random forests and regression models
😇Deploy models
😇Use PyTorch, the world’s fastest growing deep learning software, plus popular libraries like fastai and Hugging Face
Course Link
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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*This channel belongs to @bigdataspecialist group
This super amazing😱 free course😍 is designed for people with some coding experience who want to learn how to apply deep learning and machine learning to practical problems🤩.
Here's what you will be learning from this course😉:
😇Build and train deep learning models for computer vision, natural language processing, tabular analysis, and collaborative filtering problems
😇Create random forests and regression models
😇Deploy models
😇Use PyTorch, the world’s fastest growing deep learning software, plus popular libraries like fastai and Hugging Face
Course Link
#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python
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Google's Making Friends with Machine Learning Course By Cassie Kozyrkov
This course is an absolute👌 gem⭐️
You can now enjoy all 6.5 hours🤩 of Google’s legendary🤯 AI course designed to enlighten AI beginners, grow technology leaders, inform better citizens, and amuse🤭 AI experts!
Are you as excited😃 as I am?😊
Click This Link
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This course is an absolute👌 gem⭐️
You can now enjoy all 6.5 hours🤩 of Google’s legendary🤯 AI course designed to enlighten AI beginners, grow technology leaders, inform better citizens, and amuse🤭 AI experts!
Are you as excited😃 as I am?😊
Click This Link
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YouTube
Making Friends with Machine Learning: The Entire Course
All in one place: the best AI course you’ve ever watched!
You can now enjoy all 6.5 hours of Google’s legendary AI course designed to enlighten AI beginners, grow technology leaders, inform better citizens, and amuse AI experts!
This video is the feast…
You can now enjoy all 6.5 hours of Google’s legendary AI course designed to enlighten AI beginners, grow technology leaders, inform better citizens, and amuse AI experts!
This video is the feast…