Silhouette coefficient: A score from -1 to 1 describing the clusters found during modeling. A score near zero indicates overlapping clusters, and scores less than zero indicate data points assigned to incorrect clusters. A
Stop words: A list of words removed by natural language processing tools when building your dataset. There is no single universal list of stop words used by all-natural language processing tools.
In supervised learning, every training sample from the dataset has a corresponding label or output value associated with it. As a result, the algorithm learns to predict labels or output values.
Test dataset: The data withheld from the model during training, which is used to test how well your model will generalize to new data.
Training dataset: The data on which the model will be trained. Most of your data will be here.
Transformer: A more modern replacement for RNN/LSTMs, the transformer architecture enables training over larger datasets involving sequences of data.
In unlabeled data, you don't need to provide the model with any kind of label or solution while the model is being trained.
In unsupervised learning, there are no labels for the training data. A machine learning algorithm tries to learn the underlying patterns or distributions that govern the data.
Stop words: A list of words removed by natural language processing tools when building your dataset. There is no single universal list of stop words used by all-natural language processing tools.
In supervised learning, every training sample from the dataset has a corresponding label or output value associated with it. As a result, the algorithm learns to predict labels or output values.
Test dataset: The data withheld from the model during training, which is used to test how well your model will generalize to new data.
Training dataset: The data on which the model will be trained. Most of your data will be here.
Transformer: A more modern replacement for RNN/LSTMs, the transformer architecture enables training over larger datasets involving sequences of data.
In unlabeled data, you don't need to provide the model with any kind of label or solution while the model is being trained.
In unsupervised learning, there are no labels for the training data. A machine learning algorithm tries to learn the underlying patterns or distributions that govern the data.
How To Use Tableau and Python
TabPy (the Tableau Python Server) is an Analytics Extension implementation that expands Tableau’s capabilities by allowing users to execute Python scripts and saved functions via Tableau’s table calculations. You can learn more about it in this article
Link: https://medium.datadriveninvestor.com/introducing-tabpy-tableau-python-e812bf3f2632
TabPy (the Tableau Python Server) is an Analytics Extension implementation that expands Tableau’s capabilities by allowing users to execute Python scripts and saved functions via Tableau’s table calculations. You can learn more about it in this article
Link: https://medium.datadriveninvestor.com/introducing-tabpy-tableau-python-e812bf3f2632
Medium
Introducing Tabpy: Tableau + Python
Machine learning and Data Science have revolutionized analytics world too. Organizations want to leverage the capabilities of ML to enhance
Importance of Theory in Data Science
While there are many resources covering the theoretical foundations of data science concepts, few demonstrate why having these foundations is practically important. This article gives four examples illustrating why it’s crucial for a data scientist to know what they’re doing
Link: https://towardsdatascience.com/the-importance-of-theory-in-data-science-3487b4e93953
While there are many resources covering the theoretical foundations of data science concepts, few demonstrate why having these foundations is practically important. This article gives four examples illustrating why it’s crucial for a data scientist to know what they’re doing
Link: https://towardsdatascience.com/the-importance-of-theory-in-data-science-3487b4e93953
Medium
The Importance of Theory in Data Science
Four examples illustrating why it’s crucial for a data scientist to know what they’re doing
A WELL CONCISED INTRODUCTION TO REINFORCEMENT LEARNING
Reinforcement Learning (RL) is the science of decision making. It is about learning the optimal behavior in an environment to obtain maximum reward. This article will guide you through understanding RL and it's applications.
Link: Read Me👀
What you will learn:
👌How RL Works
👌Examples of RL
👌Benefits of RL
👌Challenges of RL
👌Future of RL
Reinforcement Learning (RL) is the science of decision making. It is about learning the optimal behavior in an environment to obtain maximum reward. This article will guide you through understanding RL and it's applications.
Link: Read Me👀
What you will learn:
👌How RL Works
👌Examples of RL
👌Benefits of RL
👌Challenges of RL
👌Future of RL
Synopsys
What is Reinforcement Learning? – Overview of How it Works | Synopsys
Reinforcement Learning (RL) is a decision-making science where optimal behaviors are learned through interactions to maximize rewards in various environments.
Artificial Neural Networks (ANN) with Keras in Python and R
Rating ⭐️: 4.5 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 150,528
Created by: Start-Tech Academy
🔗 Course link
Linear Regression and Logistic Regression in Python
Rating ⭐️: 4.6 out of 5
Duration ⏰: 7.5 hours on-demand video
Students 👨🏫: 50,422
Created by: Start-Tech Academy
🔗 Course link
Support Vector Machines in Python: SVM Concepts & Code
Rating ⭐️: 4.7 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 80,685
Created by: Start-Tech Academy
🔗 Course link
Note: Free coupon is inserted in URL. Courses are FREE FOR FIRST 1000 enrollments
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Rating ⭐️: 4.5 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 150,528
Created by: Start-Tech Academy
🔗 Course link
Linear Regression and Logistic Regression in Python
Rating ⭐️: 4.6 out of 5
Duration ⏰: 7.5 hours on-demand video
Students 👨🏫: 50,422
Created by: Start-Tech Academy
🔗 Course link
Support Vector Machines in Python: SVM Concepts & Code
Rating ⭐️: 4.7 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 80,685
Created by: Start-Tech Academy
🔗 Course link
Note: Free coupon is inserted in URL. Courses are FREE FOR FIRST 1000 enrollments
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Udemy
Online Courses - Learn Anything, On Your Schedule | Udemy
Udemy is an online learning and teaching marketplace with over 213,000 courses and 62 million students. Learn programming, marketing, data science and more.
PYTHON FOR MACHINE LEARNING COURSE
This course is brought to you by AI Business School with the contribution of Samsung SDS and Global AI Hub for free.
In this course, you’ll learn everything you need to know to:
😃 solve real-life problems with Python and transition to machine learning and AI.
😃Work on complex programming projects efficiently, to get the data in the shape that your program needs,
😃Learn how to prepare and process your data to understand the story it holds.
😃A certificate of completion
Course Link: Click Me!!!
This course is brought to you by AI Business School with the contribution of Samsung SDS and Global AI Hub for free.
In this course, you’ll learn everything you need to know to:
😃 solve real-life problems with Python and transition to machine learning and AI.
😃Work on complex programming projects efficiently, to get the data in the shape that your program needs,
😃Learn how to prepare and process your data to understand the story it holds.
😃A certificate of completion
Course Link: Click Me!!!
Image Recognition for Beginners using CNN in R Studio
Rating ⭐️: 4.3 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 76,420
Created by: Start-Tech Academy
What you will learn:
⭐️Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning
⭐️Build an end-to-end Image recognition project in R
⭐️Learn usage of Keras and Tensorflow libraries
⭐️Use Artificial Neural Networks (ANN) to make predictions
🔗 Course link
Note: Free coupon is inserted in URL. Courses are FREE FOR FIRST 1000 enrollments
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Rating ⭐️: 4.3 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 76,420
Created by: Start-Tech Academy
What you will learn:
⭐️Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning
⭐️Build an end-to-end Image recognition project in R
⭐️Learn usage of Keras and Tensorflow libraries
⭐️Use Artificial Neural Networks (ANN) to make predictions
🔗 Course link
Note: Free coupon is inserted in URL. Courses are FREE FOR FIRST 1000 enrollments
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Udemy
Image Recognition for Beginners using CNN in R Studio
Deep Learning based Convolutional Neural Networks (CNN) for Image recognition using Keras and Tensorflow in R Studio
👉Here's an amazing self explanatory infographics that depicts the SQL Join clause with each category quite easily.
📍Types of joins used very often includes -
✔️LEFT JOIN - All data from the left table but common data from the right table
✔️RIGHT JOIN - All data from right table and common data from the left table
✔️INNER JOIN - Only common data from both the tables
✔️OUTER JOIN - All the data from both the tables keeping null values with no common keys
✔️UNION - Stack table data on top of one another
✔️CROSS JOIN - All possible combinations of data from both the tables
📍Types of joins used very often includes -
✔️LEFT JOIN - All data from the left table but common data from the right table
✔️RIGHT JOIN - All data from right table and common data from the left table
✔️INNER JOIN - Only common data from both the tables
✔️OUTER JOIN - All the data from both the tables keeping null values with no common keys
✔️UNION - Stack table data on top of one another
✔️CROSS JOIN - All possible combinations of data from both the tables
Types of Regression Analysis in Machine Learning
If you are looking to dive deeper into Regression Analysis for Machine Learning and understand how to choose the right type of regression analysis model for your project, here's an article that can help.
Link: https://www.projectpro.io/article/types-of-regression-analysis-in-machine-learning/410
If you are looking to dive deeper into Regression Analysis for Machine Learning and understand how to choose the right type of regression analysis model for your project, here's an article that can help.
Link: https://www.projectpro.io/article/types-of-regression-analysis-in-machine-learning/410
ProjectPro
Types of Regression Analysis in Machine Learning
Learn what is regression analysis and understand the different types of regression analysis techniques in machine learning.
ARTIFICIAL INTELLIGENCE FOR BEGINNERS
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Artificial Intelligence.
In this curriculum, you will learn:
⭐️Different approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (GOFAI).
⭐️Neural Networks and Deep Learning, which are at the core of modern AI. It illustrates the concepts behind these important topics using code in two of the most popular frameworks - TensorFlow and PyTorch.
⭐️Neural Architectures for working with images and text. It covers recent models but may lack a little bit on the state-of-the-art.
⭐️Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.
Course Link
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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*This channel belongs to @bigdataspecialist group
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Artificial Intelligence.
In this curriculum, you will learn:
⭐️Different approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (GOFAI).
⭐️Neural Networks and Deep Learning, which are at the core of modern AI. It illustrates the concepts behind these important topics using code in two of the most popular frameworks - TensorFlow and PyTorch.
⭐️Neural Architectures for working with images and text. It covers recent models but may lack a little bit on the state-of-the-art.
⭐️Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.
Course Link
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
Machine Learning Engineer Learning Path
Course Link
Hey there!!
Check out this Machine Learning Course from Google.
Here's what you can learn from it.
👌A Tour of Google Cloud Hands-on Labs
👌Google Cloud Big Data and Machine Learning Fundamentals
👌How Google Does Machine Learning
👌Launching into Machine Learning
👌TensorFlow on Google Cloud
👌Feature Engineering
👌Machine Learning in the Enterprise
👌Production Machine Learning Systems
😃And a lot of interesting machine learning topics
Course Link
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
Course Link
Hey there!!
Check out this Machine Learning Course from Google.
Here's what you can learn from it.
👌A Tour of Google Cloud Hands-on Labs
👌Google Cloud Big Data and Machine Learning Fundamentals
👌How Google Does Machine Learning
👌Launching into Machine Learning
👌TensorFlow on Google Cloud
👌Feature Engineering
👌Machine Learning in the Enterprise
👌Production Machine Learning Systems
😃And a lot of interesting machine learning topics
Course Link
#ai #ml #neural_networks #machine_learning #data_science #deep_learning
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Efficient Python Tricks and Tools for
Data Scientists - By Khuyen Tra
GithubRepo : https://github.com/khuyentran1401/Efficient_Python_tricks_and_tools_for_data_scientists
Stars ⭐️: 675
Forked By: 202
Data Scientists - By Khuyen Tra
GithubRepo : https://github.com/khuyentran1401/Efficient_Python_tricks_and_tools_for_data_scientists
Stars ⭐️: 675
Forked By: 202
GitHub
GitHub - khuyentran1401/Efficient_Python_tricks_and_tools_for_data_scientists: Efficient Python Tricks and Tools for Data Scientists
Efficient Python Tricks and Tools for Data Scientists - khuyentran1401/Efficient_Python_tricks_and_tools_for_data_scientists
Hello Dear😊!!!
Have you heard of The Python For Machine Learning International Bootcamp coming up on the 12th of September?
Link: Click Me
If you haven't, Global AI Hub is organizing a FREE ONE-MONTH INTENSIVE boot camp on python for machine learning.
This is a chance to improve yourselves in subjects such as Python😍, #machinelearning😍, #datascience😍, and #deeplearning😍!!!
In addition, you will be able to develop your portfolios ☺️ with the project work😃 that you will do from scratch under the guidance of mentors!!!😁
Does this look very interesting to you, click the link in this post to register
Link: Click Me
DEADLINE😱😱 : 7th September 2022
Have you heard of The Python For Machine Learning International Bootcamp coming up on the 12th of September?
Link: Click Me
If you haven't, Global AI Hub is organizing a FREE ONE-MONTH INTENSIVE boot camp on python for machine learning.
This is a chance to improve yourselves in subjects such as Python😍, #machinelearning😍, #datascience😍, and #deeplearning😍!!!
In addition, you will be able to develop your portfolios ☺️ with the project work😃 that you will do from scratch under the guidance of mentors!!!😁
Does this look very interesting to you, click the link in this post to register
Link: Click Me
DEADLINE😱😱 : 7th September 2022
Implementing DBSCAN in Python
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density-based unsupervised learning algorithm. It computes nearest neighbor graphs to find arbitrary-shaped clusters and outliers. Whereas the K-means clustering generates spherical-shaped clusters.
Learn more about working with it in this article
Link
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density-based unsupervised learning algorithm. It computes nearest neighbor graphs to find arbitrary-shaped clusters and outliers. Whereas the K-means clustering generates spherical-shaped clusters.
Learn more about working with it in this article
Link
KDnuggets
Implementing DBSCAN in Python
Density-based clustering algorithm explained with scikit-learn code example.
The Applied Data Science Lab is open for applications!
This program is oragnised by World Quant University.
The Applied Data Science Lab is a credentialed offering where students tackle real-world meaningful, and complex problems.
By completing a series of end-to-end data science projects, they build the wrangling, analysis, model-building, and communication skills to prepare them for success in data-centric careers in both the private and public sectors.
What you will cover:
⭐️Leverage Real-World Data
⭐️Access All the Tools you Need
⭐️Guides by Your Side
⭐️Develop The Skills to Build a Professional Portfolio
Link: Register for Free
This program is oragnised by World Quant University.
The Applied Data Science Lab is a credentialed offering where students tackle real-world meaningful, and complex problems.
By completing a series of end-to-end data science projects, they build the wrangling, analysis, model-building, and communication skills to prepare them for success in data-centric careers in both the private and public sectors.
What you will cover:
⭐️Leverage Real-World Data
⭐️Access All the Tools you Need
⭐️Guides by Your Side
⭐️Develop The Skills to Build a Professional Portfolio
Link: Register for Free
www.wqu.edu
WQU | Apply for the Applied Data Science Lab
Join the Applied Data Science Lab: Access application, online program requirements, course and certificate information, FAQs, and more.
DPhi Python Basics for Data Science Bootcamp
At the end of this Bootcamp you will know the following things:
➡️ Installing Anaconda and introduction to Jupyter Notebook
➡️ Getting familiar with Python syntaxes and writing your first Python program
➡️ Variables, Data Types, and Operators in Python
➡️ Data Structures and Data Types in Python
➡️ Python Functions and Packages/
Register Here
At the end of this Bootcamp you will know the following things:
➡️ Installing Anaconda and introduction to Jupyter Notebook
➡️ Getting familiar with Python syntaxes and writing your first Python program
➡️ Variables, Data Types, and Operators in Python
➡️ Data Structures and Data Types in Python
➡️ Python Functions and Packages/
Register Here
AI Planet (formerly DPhi)
Python Basics for Data Science
Learn the fundamentals of Python to kickstart your Data Science journey
Data Analyst Boot camp 2022: Get Ready to Be a Data Analyst.
Rating ⭐️: 3.8 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 24,500
Created by: TemoTech Learning Academy
🔗 Course link
SQL Boot Camp 2022: Complete SQL Course
Rating ⭐️: 4.1 out of 5
Duration ⏰: 4 hours on-demand video
Students 👨🏫: 10,304
Created by: Temo Tech Academy
🔗 Course link
SQL Course 2022: SQL for Data Analysis and Data Science.
Rating ⭐️: 3.4 out of 5
Duration ⏰: 5.5hours on-demand video
Students 👨🏫: 110,841
Created by: TemoTech Learning Academy
🔗 Course link
#sql #datascience #datanalysis
Rating ⭐️: 3.8 out of 5
Duration ⏰: 11 hours on-demand video
Students 👨🏫: 24,500
Created by: TemoTech Learning Academy
🔗 Course link
SQL Boot Camp 2022: Complete SQL Course
Rating ⭐️: 4.1 out of 5
Duration ⏰: 4 hours on-demand video
Students 👨🏫: 10,304
Created by: Temo Tech Academy
🔗 Course link
SQL Course 2022: SQL for Data Analysis and Data Science.
Rating ⭐️: 3.4 out of 5
Duration ⏰: 5.5hours on-demand video
Students 👨🏫: 110,841
Created by: TemoTech Learning Academy
🔗 Course link
#sql #datascience #datanalysis
Udemy
Data Analyst Boot camp 2023: Get Ready to Be a Data Analyst.
Using PostgreSQL , Real world Database & Python For Data Analysis & Data Science from scratch with Challenge& Projects .
FREE UDEMY COURSES
Complete Linear Regression Analysis in Python
Rating ⭐️: 4.5 out of 5
Duration ⏰: 7.5 hours on-demand video
Students 👨🏫: 150,747
Created by: Star Tech Academy
🔗 Course link
Data Analytics A-Z with Python
Rating ⭐️: 4.1 out of 5
Duration ⏰: 4 hours on-demand video
Students 👨🏫: 56,145
Created by: Yaswanth Sai Palaghat
🔗 Course link
Object Detection Web App with TensorFlow, OpenCV and Flask
Rating ⭐️: 4.6 out of 5
Duration ⏰: 1 hour on-demand video
Students 👨🏫: 32,020
Created by: Yaswanth Sai Palaghat
🔗 Course link
Logistic Regression in R Studio
Rating ⭐️: 4.6 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 82,771
Created by: Star Tech Academy
🔗 Course link
Logistic Regression in Python
Rating ⭐️: 4.3 out of 5
Duration ⏰: 7.5hours on-demand video
Students 👨🏫: 95,949
Created by: Star Tech Academy
🔗 Course link
#python #datanalysis #data_science #deep_learning #machinelearning
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Complete Linear Regression Analysis in Python
Rating ⭐️: 4.5 out of 5
Duration ⏰: 7.5 hours on-demand video
Students 👨🏫: 150,747
Created by: Star Tech Academy
🔗 Course link
Data Analytics A-Z with Python
Rating ⭐️: 4.1 out of 5
Duration ⏰: 4 hours on-demand video
Students 👨🏫: 56,145
Created by: Yaswanth Sai Palaghat
🔗 Course link
Object Detection Web App with TensorFlow, OpenCV and Flask
Rating ⭐️: 4.6 out of 5
Duration ⏰: 1 hour on-demand video
Students 👨🏫: 32,020
Created by: Yaswanth Sai Palaghat
🔗 Course link
Logistic Regression in R Studio
Rating ⭐️: 4.6 out of 5
Duration ⏰: 6 hours on-demand video
Students 👨🏫: 82,771
Created by: Star Tech Academy
🔗 Course link
Logistic Regression in Python
Rating ⭐️: 4.3 out of 5
Duration ⏰: 7.5hours on-demand video
Students 👨🏫: 95,949
Created by: Star Tech Academy
🔗 Course link
#python #datanalysis #data_science #deep_learning #machinelearning
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Udemy
Complete Linear Regression Analysis in Python
Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also