ChatGPT for Deep Learning with Python Keras and Tensorflow

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Free Download ChatGPT for Deep Learning with Python Keras and Tensorflow
Published 6/2024
Created by Alexander Hagmann
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 190 Lectures ( 14h 31m ) | Size: 7.2 GB

Master Image Recognition, Time Series Prediction, Regression and Classification with ChatGPT! A Project-based Course.
What you'll learn:
Utilize ChatGPT for real-life Data Science and Deep Learning projects
Let ChatGPT do the coding work for you (Python, Pandas, Keras etc.)
Use ChatGPT to select the most suitable Neural Network for your task
Utilize ChatGPT to analyse and interpret the outcomes of your Deep Learning models
Ask ChatGPT to critically assess and improve your Neural Networks
Perform an Explanatory Data Analysis with ChatGPT and Python
Use ChatGPT for Data Manipulation, Aggregation, advanced Pandas coding & more
Utilize ChatGPT to fit, evaluate and optimize FNN, CNN, RNN and LSTM models
Utilize ChatGPT for Regression and Classification tasks using Keras & Tensorflow
Utilize ChatGPT for Image Recognition
Utilize ChatGPT for Time Series Prediction
Use ChatGPT for Error Handling and Troubleshooting
Requirements:
An internet connection capable of streaming HD videos.
Some Data Science or Machine Learning related background (not required but it helps)
First Experience with Python and the Python Data Science Ecosystem (not required but it helps)
Description:
Welcome to a game-changing learning experience with "ChatGPT for Deep Learning using Python Keras and TensorFlow". This unique course combines the power of ChatGPT with the technical depth of Python, Keras, and TensorFlow to offer you an innovative approach to tackling complex Deep Learning projects. Whether you're a beginner or a seasoned Data Scientist, this course will significantly enhance your skill set, making you more proficient and efficient in your work.Why This Course?Deep learning and Artificial Intelligence are revolutionizing industries across the globe, but mastering these technologies often requires a significant time investment (for theory and coding). This course cuts through the complexity, leveraging ChatGPT to simplify the learning curve and expedite your project execution. You'll learn how to harness the capabilities of AI to streamline tasks from data processing to complex model training, all without needing exhaustive prior knowledge of the underlying mathematics and Python code.Comprehensive Learning ObjectivesBy the end of this course, you will be able to apply the most promising ChatGPT prompting strategies and techniques in real-world scenarios:ChatGPT Integration: Utilize ChatGPT effectively to automate and enhance various stages of your Data Science projects, including coding, model development, and result analysis.Data Management: Master techniques for loading, cleaning, and visualizing data using Python libraries like Pandas, Matplotlib, and Seaborn.Deep Learning Modeling: Gain hands-on experience in constructing and fine-tuning Neural Networks for tasks such as Image Recognition with CNNs, Time Series prediction with RNNs and LSTMs, and classification and regression with Feedforward Neural Networks (FNN), using ChatGPT as your assistant.Advanced Techniques: Learn how to best utilize ChatGPT to select the best Neural Network architecture for your projects. Optimize your models with techniques like Hyperparameter Tuning and Regularization, and enhance your models' performance with strategies like Data Augmentation.Theoretical Foundations: While the course emphasizes practical skills, you'll also gain a clear understanding of the theoretical underpinnings of the models you're using, helping you make informed decisions about your approach to each project.Course StructureThis course is structured around interactive, project-based learning. Each module is designed as a "Do-It-Yourself" project that challenges you to apply what you've learned in real-time. You'll receive:Detailed Project Assignments: These assignments mimic real-world problems and are designed to test your application of the course material.Supporting Materials: Access to a wealth of resources, including sample prompts for ChatGPT, code snippets, and datasets.Video Solutions: At the end of each project, a detailed video solution will guide you through the expected outcomes and provide additional insights.Prompting Strategies: Exclusive content on effective prompting for both GPT-3.5 (free) and GPT-4 (paid), helping you maximize your use of these powerful tools.Who Should Enroll?Data Science Beginners: If you are new to Data Science and Deep Learning, this course offers a friendly introduction to complex concepts and applications, significantly reducing your learning time.Experienced Data Scientists and Analysts: For those looking to enhance their productivity and incorporate cutting-edge AI tools into their workflows, this course provides advanced strategies and techniques to streamline and optimize your projects.Are You Ready to Revolutionize Your Data Science Capabilities?Enroll now to begin your journey at the forefront of artificial intelligence and deep learning innovation. Transform your professional capabilities and embrace the future of AI with confidence!
Who this course is for:
Beginners seeking to master real-life Data Science Projects in no time without the need to learn everything from scratch.
Data Scientists interested in boosting their work with Artificial Intelligence and Neural Networks
Everybody in a Data-related Profession wanting to leverage the power of ChatGPT for their day-to-day work.
Data Analysts seeking to outsource the most time-consuming parts of their work to ChatGPT.
Machine Learning / Deep Learning Wizards needing help and assistance for their models from ChatGPT.
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ChatGPT for Deep Learning with Python Keras and Tensorflow
Published 6/2024
Created by Alexander Hagmann
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 190 Lectures ( 14h 31m ) | 7.2 GB​

Master Image Recognition, Time Series Prediction, Regression and Classification with ChatGPT! A Project-based Course.

What you'll learn:
Utilize ChatGPT for real-life Data Science and Deep Learning projects
Let ChatGPT do the coding work for you (Python, Pandas, Keras etc.)
Use ChatGPT to select the most suitable Neural Network for your task
Utilize ChatGPT to analyse and interpret the outcomes of your Deep Learning models
Ask ChatGPT to critically assess and improve your Neural Networks
Perform an Explanatory Data Analysis with ChatGPT and Python
Use ChatGPT for Data Manipulation, Aggregation, advanced Pandas coding & more
Utilize ChatGPT to fit, evaluate and optimize FNN, CNN, RNN and LSTM models
Utilize ChatGPT for Regression and Classification tasks using Keras & Tensorflow
Utilize ChatGPT for Image Recognition
Utilize ChatGPT for Time Series Prediction
Use ChatGPT for Error Handling and Troubleshooting

Requirements:
An internet connection capable of streaming HD videos.
Some Data Science or Machine Learning related background (not required but it helps)
First Experience with Python and the Python Data Science Ecosystem (not required but it helps)

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Deep Learning With Keras and TensorFlow
Duration: 2h 36m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 829 MB
Genre: eLearning | Language: English​

All about Deep Learning!

What you'll learn:
Understand TensorFlow in detail
Define Convolutional Network
Describe Recurrent Neural Network
Explain the Restricted Boltzmann Machine (RBM)
Explain Autoencoders in detail

Requirements:
No prerequisites are required, as the course covers the concepts from the scratch. However, basic knowledge of Python and Machine Learning would help.

Description:
About the Course:

The "Deep Learning with Keras and TensorFlow" course is an intermediate level course, curated exclusively for both beginners and professionals.
The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task.

Learning Objectives:

By the end of the course, you will be able to learn about:
Introduction to TensorFlow
TF2x and Eager Execution
TensorFlow Hello World
Linear Regression With TensorFlow
Logistic Regression With TensorFlow
Intro to Deep Learning
Deep Neural Networks
Intro to Convolutional Networks
CNN for Classifications
CNN Architecture
Understanding Convolutions
CNN with MNIST Dataset
The Sequential Problem
The RNN Model
The LSTM Model
LTSM Basics
Applying RNNs to Language Modeling
LSTM Language Modeling
Intro to RBMs
Training RBMs
RBM with MNIST
Introduction to Autoencoders
Autoencoder structure
.and much more!
If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.
If you are a programmer looking to switch into an exciting new career track, this course will teach you the basic techniques used by real-world industry Machine Learning and Deep Learning developers. These are topics any successful technologist absolutely needs to know about, so what are you waiting for?

Who this course is for:
Candidates who are willing to learn Deep Learning from scratch
IT professional willing to upskill themselves in Deep Learning
Python developers willing to upskill themselves
Data Scientist or Machine Learning Developers willing to upskill themselves
IT professions willing to start the career in Deep Learning

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