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Amit Yadav
Machine Learning Instructor
Coursera Project Network
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Bio
Amit is a Machine Learning Engineer with an interest in building machine learning products. He has led a number of machine learning projects at different companies - ranging from startups to large multinational corporations.
Courses
Image Classification with CNNs using Keras
Save, Load and Export Models with Keras
Visualizing Filters of a CNN using TensorFlow
Creating Multi Task Models With Keras
Object Detection with Amazon Sagemaker
Image Data Augmentation with Keras
Classification with Transfer Learning in Keras
Starting GUI Programming with JavaFX
Deploy Models with TensorFlow Serving and Flask
Object Localization with TensorFlow
Create Your First Chatbot with Rasa and Python
Create Your First Web App with Python and Flask
Linear Regression with Python
Visualizing Citibike Trips with Tableau
Siamese Network with Triplet Loss in Keras
Create Your First Python Program From UST
Regression with Automatic Differentiation in TensorFlow
Tweet Emotion Recognition with TensorFlow
Using TensorFlow with Amazon Sagemaker
Avoid Overfitting Using Regularization in TensorFlow
Logistic Regression with Python and Numpy
Hyperparameter Tuning with Neural Network Intelligence
Getting Started with Power BI Desktop
Hyperparameter Tuning with Keras Tuner
Neural Network from Scratch in TensorFlow
Predicting House Prices with Regression using TensorFlow
Detecting COVID-19 with Chest X-Ray using PyTorch
Create a Superhero Name Generator with TensorFlow
Semantic Segmentation with Amazon Sagemaker
Understanding Deepfakes with Keras
Image Noise Reduction with Auto-encoders using TensorFlow
Creating Custom Callbacks in Keras
Custom Prediction Routine on Google AI Platform
Simple Recurrent Neural Network with Keras
Basic Image Classification with TensorFlow
Neural Style Transfer with TensorFlow
Image Classification with Amazon Sagemaker
Neural Network Visualizer Web App with Python
Create Custom Layers in Keras
Basic Sentiment Analysis with TensorFlow
Create Your First Game with Python
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