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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
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 - CodeCutTech/Efficient_Python_tricks_and_tools_for_data_scientists: Efficient Python Tricks and Tools for Data Scientists
Efficient Python Tricks and Tools for Data Scientists - CodeCutTech/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
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 2024: Get Ready to Be a Data Analyst.
Become a Data Analysis Hero: Learn Python and SQL with Examples, Challenges, Projects, ChatGPT AI Generative Assistance.
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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
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
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
Udemy
Complete Linear Regression Analysis in Python
Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also
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