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Linear Regression and Logistic Regression in Python
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Support Vector Machines in Python: SVM Concepts & Code
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Rating βοΈ: 4.5 out of 5
Duration β°: 11 hours on-demand video
Students π¨βπ«: 150,528
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Linear Regression and Logistic Regression in Python
Rating βοΈ: 4.6 out of 5
Duration β°: 7.5 hours on-demand video
Students π¨βπ«: 50,422
Created by: Start-Tech Academy
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Support Vector Machines in Python: SVM Concepts & Code
Rating βοΈ: 4.7 out of 5
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Udemy
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Udemy is an online learning and teaching marketplace with over 213,000 courses and 62 million students. Learn programming, marketing, data science and more.
Image Recognition for Beginners using CNN in R Studio
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Rating βοΈ: 4.3 out of 5
Duration β°: 11 hours on-demand video
Students π¨βπ«: 76,420
Created by: Start-Tech Academy
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βοΈGet a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning
βοΈBuild an end-to-end Image recognition project in R
βοΈLearn usage of Keras and Tensorflow libraries
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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
ARTIFICIAL INTELLIGENCE FOR BEGINNERS
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Artificial Intelligence.
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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:
βοΈDifferent approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (GOFAI).
βοΈNeural 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.
βοΈNeural Architectures for working with images and text. It covers recent models but may lack a little bit on the state-of-the-art.
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Machine Learning Engineer Learning Path
Course Link
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Course Link
Hey there!!
Check out this Machine Learning Course from Google.
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πA Tour of Google Cloud Hands-on Labs
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Course Link
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Complete Linear Regression Analysis in Python
Rating βοΈ: 4.5 out of 5
Duration β°: 7.5 hours on-demand video
Students π¨βπ«: 150,747
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Data Analytics A-Z with Python
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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
FREE UDEMY COURSES
Artificial Neural Networks (ANN) with Keras in Python and R
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Artificial Neural Networks (ANN) with Keras in Python and R
Rating βοΈ: 4.3 out of 5
Duration β°: 11 hours on-demand video
Students π¨βπ«: 153,510
Created by: Star Tech Academy
π Course link
Marketing Analytics: Forecasting Models with Excel
Rating βοΈ: 4.5 out of 5
Duration β°: 7 hours on-demand video
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Decision Trees, Random Forests, Bagging & XGBoost: R Studio
Rating βοΈ: 4.6 out of 5
Duration β°: 6 hours on-demand video
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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
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1) Data Science 101
Rating βοΈ: 5.6k+
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TENSORFLOW FREE LEARNING RESOURCES
1) Hello, TensorFlow!
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1) Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
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OβReilly Media
Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
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.
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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.
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freeCodeCamp.org
Learn PyTorch for Deep Learning β 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...
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This super amazingπ± free courseπ is designed for people with some coding experience who want to learn how to apply deep learning and machine learning to practical problemsπ€©.
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πBuild and train deep learning models for computer vision, natural language processing, tabular analysis, and collaborative filtering problems
πCreate random forests and regression models
πDeploy models
πUse PyTorch, the worldβs fastest growing deep learning software, plus popular libraries like fastai and Hugging Face
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Introduction to Neural Networks and Deep Learning Course
Expand your knowledge and skills in Neural Networks and Deep Learning with this online free course. Build and train deep neural networks for industry-related problems using key calculations that underlie deep learning
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Expand your knowledge and skills in Neural Networks and Deep Learning with this online free course. Build and train deep neural networks for industry-related problems using key calculations that underlie deep learning
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Great Learning
Neural Networks and Deep Learning - Free Course - Great Learning
Neural Networks and Deep Learning: Take up this free Deep Learning course and learn about its applications. Enrol today and get free online certificate.
Udacity Artificial Intelligence Course
Here's an interesting course where youβll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
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Here's an interesting course where youβll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
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Introduction to Tensorflow and Keras
Enroll in this TensorFlow and Keras course to gain in-depth knowledge of TensorFlow, Keras, Neural Networks, and CNN. Learn to solve Deep Learning problems through sample demonstrations.
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Enroll in this TensorFlow and Keras course to gain in-depth knowledge of TensorFlow, Keras, Neural Networks, and CNN. Learn to solve Deep Learning problems through sample demonstrations.
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Great Learning
Tensorflow and Keras Free Course With Certificate For Beginners
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Creator: ashishpatel26
Stars βοΈ: 10.7K
Forked By: 3.2K
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GitHub
GitHub - ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code: 500 AI Machine learning Deepβ¦
500 AI Machine learning Deep learning Computer vision NLP Projects with code - ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
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DIVE INTO DEEP LEARNING ||d2l.ai
Here's an Interactive deep learning book with code, math, and discussions.
Implemented with PyTorch, NumPy/MXNet, and TensorFlow.
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Here's an Interactive deep learning book with code, math, and discussions.
Implemented with PyTorch, NumPy/MXNet, and TensorFlow.
Book Link : https://d2l.ai/
GitHub Repo: https://github.com/d2l-ai/d2l-en
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Binary Classification: A Deep Learning Approach
Unlock the power to predict the future with binary classification. This tutorial will guide you through the process of distinguishing between two outcomes using Deep Learning.
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Unlock the power to predict the future with binary classification. This tutorial will guide you through the process of distinguishing between two outcomes using Deep Learning.
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Kaggle
Binary Classification
Explore and run machine learning code with Kaggle Notebooks | Using data from DL Course Data
Data Science Interview Resource
Looking to ace that Data Science Interview?
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Looking to ace that Data Science Interview?
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GitHub
GitHub - youssefHosni/Data-Science-Interview-Questions-Answers: Curated list of data science interview questions and answers
Curated list of data science interview questions and answers - youssefHosni/Data-Science-Interview-Questions-Answers
βοΈ 15 Best Machine Learning Cheat Sheet βοΈ
1- Supervised Learning
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7- Linear Algebra and Calculus
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf
8- Data Science Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf
9- Keras Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png
12- Skicit-Learn Python Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
13- Scikit-learn Cheat Sheet: Choosing the Right Estimator
https://scikit-learn.org/stable/tutorial/machine_learning_map/
14- Tensorflow Cheat Sheet
https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf
15- Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
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1- Supervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf
2- Unsupervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf
3- Deep Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf
4- Machine Learning Tips and Tricks
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf
5- Probabilities and Statistics
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf
6- Comprehensive Stanford Master Cheat Sheet
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf
7- Linear Algebra and Calculus
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf
8- Data Science Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf
9- Keras Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png
12- Skicit-Learn Python Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
13- Scikit-learn Cheat Sheet: Choosing the Right Estimator
https://scikit-learn.org/stable/tutorial/machine_learning_map/
14- Tensorflow Cheat Sheet
https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf
15- Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
#machine_learning #deep_learning #scikit-learn #keras
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GitHub
stanford-cs-229-machine-learning/en/cheatsheet-supervised-learning.pdf at master Β· afshinea/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning - afshinea/stanford-cs-229-machine-learning
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you can run on the browser with IPython.
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you can run on the browser with IPython.
Explore from 1000+ ready code templates to kickstart your AI projects
βοΈClassification
βοΈRegression
βοΈClustering
π Source link
#ai #ml #data_science #deep_learning
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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 Googleβs 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.
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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 Googleβs 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.
π Free Online Course
RatingβοΈ: 4.7 out 5
π¬ video lesson
πββοΈ Self paced
Duration β°: More than 7 hours worth of material
Source: cognitiveclass
π Course Link
#deep_Learning
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cognitiveclass.ai
Accelerating Deep Learning with GPUs
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.