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

#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #pythoasks.

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Udacity Artificial Intelligence Course

Here's an interesting course where you’ll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.

Course Link: Enroll Now

#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python


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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.

Course Link

#machine_learning #datascience #datanalysis #neural_networks #deep_learning #ai #python


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🔥🔥Build GPT: from scratch, in code, spelled out🔥🔥.

If you're a beginner interested in learning about Neural Networks, Andrej Karpathy Youtube-series on  "Neural Networks: Zero to Hero" can introduce you to the basics of Neural Networks and language modeling.

Already have this knowledge and want to do an amazing project?😍
His new course on how to build your own GPT!😱 from scratch is a must watch.

Link: https://youtu.be/kCc8FmEb1nY

Interesting not only for beginners, but for pro's as well to recap and grab new details

#ai #deeplearning #neuralnetworks #gpt


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1000 Data Science Projects
you can run on the browser with IPython.

Explore from 1000+ ready code templates to kickstart your AI projects
⭐️Classification
⭐️Regression
⭐️Clustering

🔗 Source link

#ai #ml #data_science #deep_learning

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Data Science Engineering, your way

An introduction to different Data Science engineering concepts and Applications using Python and R
These series of tutorials on Data Science engineering will try to compare how different concepts in the discipline can be implemented in the two dominant ecosystems nowadays: R and Python.

We will do this from a neutral point of view. Our opinion is that each environment has good and bad things, and any data scientist should know how to use both in order to be as prepared as posible for job market or to start personal project.

To get a feeling of what is going on regarding this hot topic, we refer the reader to DataCamp's Data Science War infographic. Their infographic explores what the strengths of R are over Python and vice versa, and aims to provide a basic comparison between these two programming languages from a data science and statistics perspective.

Far from being a repetition from the previous, our series of tutorials will go hands-on into how to actually perform different data science taks such as working with data frames, doing aggregations, or creating different statistical models such in the areas of supervised and unsupervised learning.

We will use real-world datasets, and we will build some real data products. This will help us to quickly transfer what we learn here to actual data analysis situations.

Link

#ai #ml #data_science

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MIT 6.S191: Introduction to Deep Learning 2021
Created by MIT
29 hours worth of material
🎬 43 Video lessons
👨‍🏫 Teacher: Alexander Amini
🔗 Course link

#deeplearning #ai #MIT

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Artificial Neural Network for Regression

Rating ⭐️: 4.6 out of 5
Duration : 1hr 11min on-demand video
Students 👨‍🏫: 49,827
Created by: Hadelin de Ponteves, SuperDataScience Team, Ligency Team

🔗 Course link


#ai #ml #neural_networks #machine_learning #data_science #regression

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🔥FREE COURSE ON GENERATIVE AI🔥

Interested in learning about GENERATIVE AI?🔥

Here's a free course from Google.

Link

#generative #ai #ml #ai


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