Deep Learning-101
5.0
(3)
22 learners
What you'll learn
This course includes
- 42.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 98 lessons • 42.5 hours of video
Deep Learning-101
98 lessons
• 42.5 hours
Deep Learning-101
98 lessons
• 42.5 hours
- Deep Learning | Deep Learning-101 complete course | (Day-01) 01:07:45
- Introduction to Deep Learning 05:00
- Machine Learning vs. Deep Learning 13:58
- Small Data vs. Big Data for Deep Learning 02:30
- What is a Neural Network? 21:17
- Types of Neural Network 07:07
- Architecture of Neural Networks 04:34
- Single Layer vs. Multilayer Neural Network 03:16
- Multi Layer Perceptron in Deep Learning 16:25
- Types of Multi Layer Perceptron 09:50
- Applications of Multi layer perceptron 04:29
- Python Libraries for Deep Learning 17:03
- Ten steps to create a neural Network in Python with TensorFlow 10:52
- Build Neural Networks in Python with TensorFlow 24:01
- GPU for Deep Learning with TensorFlow 03:21
- Build a Multilayer Perceptron in Python with TensorFlow 13:25
- Call Back Function for Early Stopping of epochs 07:47
- How many neurons should be in each layer | verbose | batch size 08:36
- Step & Sigmoid Activation functions for Artificial Neural Network 54:10
- tanH, ReLu, Leaky Relu, Paramteric ReLu Activation Function 25:53
- SoftMax activation functions 10:30
- How to choose an activation function? 17:29
- Case Studies in Python | Deep Learning-101 complete course | (Day-04) 01:55:40
- Case Studies in Python | Deep Learning-101 complete course | (Day-05) 01:15:51
- Case Study on UCI Heart Disease Data Project 1 24:51
- Case Study on UCI Heart Disease Data Project 2 34:39
- Case Study on UCI Heart Disease Data Project 3 23:11
- Case Study on UCI Heart Disease Data Project 4 10:23
- Competitions and Assignments for the course 10:56
- Job Ready AI course Complete announcement 03:21
- Case Study for Kaggle Competition 01:04:07
- What is random seeding or Random State in ML? 02:29
- Case Study on Bank Churn Dataset 01:05:05
- Important Assignment for Kaggle Competitions 00:57
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-1 15:03
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-2 35:06
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-3 36:53
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-4 26:57
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-5 01:01:29
- Convolutional Neural Network (CNN) in Python with TensorFlow | Part-6 31:10
- Introduction to Computer Vision 30:19
- Computer vision in Python 22:05
- Assignment for CNN before next class 01:06
- Introduction | Recurrent Neural Network (Part-1) 14:05
- All about Recurrent Neural Network (Part-2) 58:42
- RNN in Python | Recurrent Neural Network (Part-3) 17:33
- Natural Language Processing NLP introduction in urdu hindi 01:01:47
- Sentiment Analysis | NLP | In python 46:29
- LSTM (Long Short Term Memory) for NLP 27:05
- History of ANN, CNN, RNN, LSTM, GRU 50:16
- LSTM vs. GRU types of RNN for Deep learning in NLP 24:41
- Introduction to Time Series Data Analysis in python 01:09:47
- Data Analysis Types for Time Series Data 32:04
- Types of Data about Time and Time series 05:09
- Time series analysis and plotting in python 28:51
- Time Series Project understanding and development 51:25
- Time series Weather forecasting project (1/3) 01:12:31
- Time series Weather forecasting project (2/3) 01:21:36
- Time series Weather forecasting project (3/3) 17:14
- prophet model from FB (meta) for time series analysis (1/2) 01:07:57
- prophet model from FB (meta) for time series analysis (2/2) 18:58
- Web-scrapping in #urdu #hindi with python (1/2) 32:30
- Web-scrapping in #urdu #hindi with python (2/2) 26:21
- Stock market data scrapping using python 23:04
- ARIMA, SARIMA, SARIMAX in python complete project 01:04:15
- Paddy Rice Disease Detection using CNN models in TensorFlow with Python 54:43
- Underfitting of a machine learning model 07:50
- Overfitting of a machine learning model 06:38
- Good fit or Robus Model explained in urdu/hindi 04:37
- How to improve a ML/DL model fitness? 08:38
- Improving an overfit model in Machine/Deep Learning 23:39
- Transfer Learning and pre-trained Models 19:55
- Transfer Learning in python using TensorFlow/Keras 17:05
- Assignment Alert for Course Students 01:02
- Generative AI | Introduction 13:08
- Generative AI | Key Terms 33:04
- Generative AI | How does it Work? 07:14
- Generative AI in 2024 15:01
- Generative AI | Will my job be taken away? 05:44
- Pre-trained Models and Image Classification | Transfer Learning 44:37
- Transfer learning in python with TensorFlow | A complete Project 30:27
- Progressive growing GANs (pro-GANs) in TensorFlow 51:05
- Assignment Alert 02:33
- TensorBoard for Hyperparameter Tuning of Deep Learning Models 38:47
- Introduction | Diffusion models for Generative AI (1/3) 17:14
- Stable Diffusion model in Python with TensorFlow locally 21:38
- SORA open AI model for Video Generation 10:17
- Important IDs to make before next lecture 03:45
- Introduction to prompt engineering 24:36
- Types of Prompt engineering or prompts designing 08:06
- Prompt designing strategies to get full potential of LLMs 11:48
- Generate prompts from LLMs 08:09
- LLMs and prompt engineering live demo for webapp development 44:03
- Use pre trained models from Huggingface 33:08
- Introduction to API (Application Programming Interface) 25:30
- LangChain workflow for LLMs 09:20
- Applications of LangChain for LLMs 07:47
- LangChain + OpenAI API + HuggingFace API 15:43
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