Python Data Science Tutorial (English) (Part 3)

   Monday, May 06, 2024   

Starting a new Lecture Notes Series on Python Data Science Tutorial

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Channel Name: codebasics

So Let Us Start to This Journey of Learning 

Python Data Science Tutorial By Lecture Notes together!

Lecture 85: Loss or Cost Function | Deep Learning Tutorial 11 (Tensorflow Tutorial, Keras & Python)

Lecture 86: Gradient Descent For Neural Network | Deep Learning Tutorial 12 (Tensorflow2.0, Keras & Python)

Lecture 87: Implement Neural Network In Python | Deep Learning Tutorial 13 (Tensorflow2.0, Keras & Python)

Lecture 88: Stochastic Gradient Descent vs Batch Gradient Descent vs Mini Batch Gradient Descent |DL Tutorial 14

Lecture 89: Chain Rule | Deep Learning Tutorial 15 (Tensorflow2.0, Keras & Python)

Lecture 90: Tensorboard Introduction | Deep Learning Tutorial 16 (Tensorflow2.0, Keras & Python)

Lecture 91: GPU bench-marking with image classification | Deep Learning Tutorial 17 (Tensorflow2.0, Python)

Lecture 92: Customer churn prediction using ANN | Deep Learning Tutorial 18 (Tensorflow2.0, Keras & Python)

Lecture 93: Precision, Recall, F1 score, True Positive|Deep Learning Tutorial 19 (Tensorflow2.0, Keras & Python)

Lecture 94: Handling imbalanced dataset in machine learning | Deep Learning Tutorial 21 (Tensorflow2.0 & Python)

Lecture 95: Applications of computer vision | Deep Learning Tutorial 22 (Tensorflow2.0, Keras & Python)

Lecture 96: Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)

Lecture 97: Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python)

Lecture 98: Convolution padding and stride | Deep Learning Tutorial 25 (Tensorflow2.0, Keras & Python)

Lecture 99: Data augmentation to address overfitting | Deep Learning Tutorial 26 (Tensorflow, Keras & Python)

Lecture 100: Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python)

Lecture 101: Image classification vs Object detection vs Image Segmentation | Deep Learning Tutorial 28

Lecture 102: Popular datasets for computer vision: ImageNet, Coco and Google Open images | Deep Learning 29

Lecture 103: Sliding Window Object Detection | Deep Learning Tutorial 30 (Tensorflow, Keras & Python)

Lecture 104: What is YOLO algorithm? | Deep Learning Tutorial 31 (Tensorflow, Keras & Python)

Lecture 105: Object detection using YOLO v4 and pre trained model | Deep Learning Tutorial 32 (Tensorflow)

Lecture 106: What is Recurrent Neural Network (RNN)? Deep Learning Tutorial 33 (Tensorflow, Keras & Python)

Lecture 107: Types of RNN | Recurrent Neural Network Types | Deep Learning Tutorial 34 (Tensorflow & Python)

Lecture 108: Vanishing and exploding gradients | Deep Learning Tutorial 35 (Tensorflow, Keras & Python)

Lecture 109: Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)

Lecture 110: Simple Explanation of GRU (Gated Recurrent Units) | Deep Learning Tutorial 37 (Tensorflow & Python)

Lecture 111: Bidirectional RNN | Deep Learning Tutorial 38 (Tensorflow, Keras & Python)

Lecture 112: Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python)

Lecture 113: Word embedding using keras embedding layer | Deep Learning Tutorial 40 (Tensorflow, Keras & Python)

Lecture 114: What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python)

Lecture 115: Word2Vec Part 2 | Implement word2vec in gensim | | Deep Learning Tutorial 42 with Python

Lecture 116: Distributed Training On NVIDIA DGX Station A100 | Deep Learning Tutorial 43 (Tensorflow & Python)

Lecture 117: Tensorflow Input Pipeline | tf Dataset | Deep Learning Tutorial 44 (Tensorflow, Keras & Python)

Lecture 118: Optimize Tensorflow Pipeline Performance: prefetch & cache | Deep Learning Tutorial 45 (Tensorflow)

Lecture 119: What is BERT? | Deep Learning Tutorial 46 (Tensorflow, Keras & Python)

Lecture 120: Text Classification Using BERT & Tensorflow | Deep Learning Tutorial 47 (Tensorflow, Keras & Python)

Lecture 121: tf serving tutorial | tensorflow serving tutorial | Deep Learning Tutorial 48 (Tensorflow, Python)

Lecture 12: Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)