categorizedDLContent.js

const categorizedDLVideos = {
    "Introduction to Deep Learning": [
        { title: "What is Deep Learning? Deep Learning Vs Machine Learning", url: "https://youtube.com/watch?v=fHF22Wxuyw4" },
        { title: "100 Days of Deep Learning | Course Announcement", url: "https://youtube.com/watch?v=2dH_qjc9mFg" },
        { title: "Types of Neural Networks | History of Deep Learning | Applications of Deep Learning", url: "https://youtube.com/watch?v=fne_UE7hDn0" }
    ],
    "Artificial Neural Networks (ANNs)": [
        { title: "What is a Perceptron? Perceptron Vs Neuron | Perceptron Geometric Intuition", url: "https://youtube.com/watch?v=X7iIKPoZ0Sw" },
        { title: "Perceptron Trick | How to train a Perceptron | Perceptron Part 2", url: "https://youtube.com/watch?v=Lu2bruOHN6g" },
        { title: "Multi Layer Perceptron | MLP Intuition", url: "https://youtube.com/watch?v=qw7wFGgNCSU" },
        { title: "Perceptron Loss Function | Hinge Loss | Binary Cross Entropy | Sigmoid Function",url:"https://youtube.com/watch?v=2_gCL5RAkHc" },
        { title: "Problem with Perceptron",url:"https://youtube.com/watch?v=Jp44b27VnOg" },
        { title: "MLP Notation", url: "https://youtube.com/watch?v=H0_3SJh4Rqs" },
        { title: "Forward Propagation | How a neural network predicts output?", url: "https://youtube.com/watch?v=7MuiScUkboE" },
        { title: "ARTICLE", url:"https://jalammar.github.io/visual-interactive-guide-basics-neural-networks/"},
        { title: "ARTICLE" , url:"https://jalammar.github.io/feedforward-neural-networks-visual-interactive/"},
        { title: "Customer Churn Prediction using ANN", url: "https://youtube.com/watch?v=9wmImImmgcI" },
        { title: "Handwritten Digit Classification using ANN", url: "https://youtube.com/watch?v=3xPT2Pk0Jds" },
        { title: "Graduate Admission Prediction using ANN", url: "https://youtube.com/watch?v=RCmiPBiA4qg" },
        { title: "Loss Functions in Deep Learning", url: "https://youtube.com/watch?v=gb5nm_3jBIo" },
        { title: "Backpropagation in Deep Learning | Part 1 | The What?", url: "https://youtube.com/watch?v=6M1wWQmcUjQ" },
        { title: "Backpropagation Part 2 | The How | Complete Deep Learning Playlist", url: "https://youtube.com/watch?v=ma6hWrU-LaI" },
        { title: "Backpropagation Part 3 | The Why | Complete Deep Learning Playlist", url: "https://youtube.com/watch?v=6xO-x8y0YSY" , articleLink:"https://home.agh.edu.pl/~vlsi/AI/backp_t_en/backprop.html", articleTitle:"Backpropagation Algorithm"},
        { title: "MLP Memoization | Complete Deep Learning Playlist", url: "https://youtube.com/watch?v=rW0eeTXas4k" },
        { title: "Gradient Descent in Neural Networks | Batch vs Stochastics vs Mini Batch Gradient Descent", url: "https://youtube.com/watch?v=7z6yXpYk7sw" },
        { title: "Vanishing Gradient Problem in ANN | Exploding Gradient Problem | Code Example", url: "https://youtube.com/watch?v=uCrevbBh0zM" },
        { title: "How to Improve the Performance of a Neural Network", url: "https://youtube.com/watch?v=Ue_6n1yT_R8" },
        { title: "Early Stopping In Neural Networks | End to End Deep Learning Course", url: "https://youtube.com/watch?v=Ygvskt5HadI" },
        { title: "Data Scaling in Neural Network | Feature Scaling in ANN | End to End Deep Learning Course", url: "https://youtube.com/watch?v=mzRO0cVppQ0" },
        { title: "Dropout Layer in Deep Learning | Dropouts in ANN | End to End Deep Learning", url: "https://youtube.com/watch?v=gyTlcHVeBjM" },
        { title: "Dropout Layers in ANN | Code Example | Regression | Classification", url: "https://youtube.com/watch?v=tgIx04ML7-Y" },
        { title: "Regularization in Deep Learning | L2 Regularization in ANN | L1 Regularization | Weight Decay in ANN", url: "https://youtube.com/watch?v=4xRonrhtkzc" },
        { title: "Activation Functions in Deep Learning | Sigmoid, Tanh and Relu Activation Function", url: "https://youtube.com/watch?v=7LcUkgzx3AY" , articleLink:"https://playground.tensorflow.org/", articleTitle:"Tensorflow Playground"},
        { title: "Great article on RELU", url:"https://builtin.com/machine-learning/relu-activation-function#:~:text=ReLU%2C%20short%20for%20rectified%20linear,neural%20networks%20in%20machine%20learning."},
        { title: "Relu Variants Explained | Leaky Relu | Parametric Relu | Elu | Selu | Activation Functions Part 2", url: "https://youtube.com/watch?v=2OwWs7Hzr9g" },
        { title: "Weight Initialization Techniques | What not to do? | Deep Learning", url: "https://youtube.com/watch?v=2MSY0HwH5Ss" },
        { title: "Xavier/Glorat And He Weight Initialization in Deep Learning", url: "https://youtube.com/watch?v=nwVOSgcrbQI" , articleLink:"https://www.deeplearning.ai/ai-notes/initialization/index.html", articleTitle:"Visualization tool by DeepLearning.ai to understand weight initialization"},
        { title: "Batch Normalization in Deep Learning | Batch Learning in Keras", url: "https://youtube.com/watch?v=2AscwXePInA" },
        { title: "Optimizers in Deep Learning | Part 1 | Complete Deep Learning Course", url: "https://youtube.com/watch?v=iCTTnQJn50E" },
        { title: "Exponentially Weighted Moving Average or Exponential Weighted Average | Deep Learning", url: "https://youtube.com/watch?v=jAqVuYJ8TP8" , articleLink:"https://medium.com/@tobias-chc/exponentially-weighted-average-5eed00181a09", articleTitle:"Exponentially Weighted Average"},
        { title: "SGD with Momentum Explained in Detail with Animations | Optimizers in Deep Learning Part 2", url: "https://youtube.com/watch?v=vVS4csXRlcQ" , articleLink:"https://machinelearningmastery.com/gradient-descent-with-momentum-from-scratch/",articleTitle:"Gradient Descent With Momentum from Scratch"},
        { title: "A must read article on SGD with momentum", url:"https://towardsdatascience.com/stochastic-gradient-descent-with-momentum-a84097641a5d"},
        { title: "Nesterov Accelerated Gradient (NAG) Explained in Detail | Animations | Optimizers in Deep Learning", url: "https://youtube.com/watch?v=rKG9E6rce1c" },
        { title: "AdaGrad Explained in Detail with Animations | Optimizers in Deep Learning Part 4", url: "https://youtube.com/watch?v=nqL9xYmhEpg" },
        { title: "RMSProp Explained in Detail with Animations | Optimizers in Deep Learning Part 5", url: "https://youtube.com/watch?v=p0wSmKslWi0" },
        { title: "Adam Optimizer Explained in Detail with Animations | Optimizers in Deep Learning Part 5", url: "https://youtube.com/watch?v=N5AynalXD9g" },
        { title: "Keras Tuner | Hyperparameter Tuning a Neural Network", url: "https://youtube.com/watch?v=oYnyNLj8RMA" },
        { title: "Article", url:"https://www.asimovinstitute.org/neural-network-zoo/", notes:"NOTE: This is a great article to understand the different types of neural networks and architechture." },
        { title:"Neural Networks by 3Blue1Brown", url:"https://www.3blue1brown.com/topics/neural-networks", notes :"NOTE: You can watch this series to understand neural networks in depth."}
    ],
    "Convolutional Neural Networks (CNNs)": [
        { title: "What is Convolutional Neural Network (CNN) | CNN Intution", url: "https://youtube.com/watch?v=hDVFXf74P-U" },
        { title: "3D Simulation", url:"https://www.youtube.com/watch?v=3JQ3hYko51Y"},
        { title: "CNN Vs Visual Cortex | The Famous Cat Experiment", url: "https://youtube.com/watch?v=aslTGS9ef98" },
        { title: "CNN Part 3 | Convolution Operation", url: "https://youtube.com/watch?v=cgJx3GvQ5y8" },
        { title: "What is Convolution", url:"https://youtu.be/KuXjwB4LzSA?si=nIqav7wLbyoa_weZ", notes:"NOTE: This is a great video to understand the concept of convolution. Its by 3Blue1Brown" ,articleLink:"https://medium.com/analytics-vidhya/convolution-operations-in-cnn-deep-learning-compter-vision-128906ece7d3", articleTitle:"Convolution Operations in CNN"},
        { title: "VISUALIZATION", url:"https://setosa.io/ev/image-kernels/", notes:"This is a great tool to visualize kernels." },
        { title: "VISUALIZATION", url:"https://www.youtube.com/watch?v=f0t-OCG79-U" },
        { title: "Padding & Strides in CNN", url: "https://youtube.com/watch?v=btWE6SsdDZA" },
        { title: "Pooling Layer in CNN | MaxPooling in Convolutional Neural Network", url: "https://youtube.com/watch?v=DwmGefkowCU" , articleLink:"https://www.youtube.com/watch?v=mW3KyFZDNIQ", articleTitle:"Max Pooling Visualization"},
        { title: "CNN Architecture | LeNet -5 Architecture", url: "https://youtube.com/watch?v=ewsvsJQOuTI" ,articleLink:"https://lunar-joke-35b.notion.site/CNN-from-Scratch-with-pure-Mathematical-Intuition-a201ef0ca1314058a1707a3ae260981e", articleTitle:"CNN from Scratch with pure  Mathematical Intuition"},
        { title: "Comparing CNN Vs ANN", url: "https://youtube.com/watch?v=niE5DRKvD_E" ,articleLink:"https://learnopencv.com/understanding-convolutional-neural-networks-cnn/", articleTitle:"Understanding Convolutional Neural Networks (CNN)"},
        { title: "Backpropagation in CNN", url: "https://youtube.com/watch?v=RvCCFttGFMY" },
        { title: "CNN Backpropagation Part 2 | How Backpropagation works on Convolution, Maxpooling and Flatten Layers", url: "https://youtube.com/watch?v=OoSDzOodY3Y" },
        { title: "Great Indepth video on CNN", url:"https://www.youtube.com/watch?v=JB8T_zN7ZC0"},
        { title: "Cat Vs Dog Image Classification Project | Deep Learning Project | CNN Project", url: "https://youtube.com/watch?v=0K4J_PTgysc"},
        { title: "Data Augmentation in Deep Learning | CNN", url: "https://youtube.com/watch?v=sM2C-SsREgM" },
        { title: "Pretrained models in CNN", url: "https://youtube.com/watch?v=0MVXteg7TB4" },
        { title: "Whad does a CNN see? | Visualizing CNN Filters and Feature Maps", url: "https://youtube.com/watch?v=WJysB1RK2vM" ,articleLink:"https://machinelearningmastery.com/how-to-visualize-filters-and-feature-maps-in-convolutional-neural-networks/",articleTitle:"How to Visualize Filters and Feature Maps in Convolutional Neural Networks"},
        { title: "Transfer Learning in Keras | Fine Tuning Vs Feature Extraction", url: "https://youtube.com/watch?v=WWcgHjuKVqA" , articleLink:"https://towardsdatascience.com/how-transfer-learning-works-a90bc4d93b5e", articleTitle:"How Transfer Learning Works" },
        { title: "Keras Functional Model | How to build non-linear Neural Networks?", url: "https://youtube.com/watch?v=OvQQP1QVru8" },
        { title: "KAGGLE COMPETITON", url:"https://www.kaggle.com/competitions/digit-recognizer", notes:"This is a good competition to participate in to implement CNNs."},
        { title: "PROJECT", url: "https://github.com/anshaneja5/doooodle", notes:"I built this project after studying CNNs. It's a doodle classifier. Check it out and try to implement it yourself."}
    ],
    "Recurrent Neural Networks (RNNs)": [
        { title: "Why RNNs are needed | RNNs Vs ANNs | RNN Part 1", url: "https://youtube.com/watch?v=4KpRP-YUw6c" },
        { title: "Recurrent Neural Network | Forward Propagation | Architecture", url:"https://youtube.com/watch?v=BjWqCcbusMM"},
        { title: "Recurrent Neural Network | Forward Propagation | Architecture", url: "https://youtube.com/watch?v=BjWqCcbusMM" },
        { title: "RNN Sentiment Analysis | RNN Code Example in Keras", url: "https://youtube.com/watch?v=JgnbwKnHMZQ" },
        { title: "Types of RNN | Many to Many | One to Many | Many to One RNNs", url: "https://youtube.com/watch?v=TkOBxzhIySg" },
        { title: "How Backpropagation works in RNN", url: "https://youtube.com/watch?v=OvCz1acvt-k" , articleLink:"http://karpathy.github.io/2015/05/21/rnn-effectiveness/",articleTitle:"The Unreasonable Effectiveness of Recurrent Neural Networks",notes:"NOTE: This is a great article by Andrej Karpathy to understand the effectiveness of RNNs."},
        { articleLink:"https://dennybritz.com/posts/wildml/recurrent-neural-networks-tutorial-part-1/", articleTitle:"Recurrent Neural Networks Tutorial"},
        { title:"RNN Article ",url:"https://madewithml.com/courses/foundations/recurrent-neural-networks/"}
    ],
    "LSTMs and GRUs": [
        { title: "LSTM | Long Short Term Memory | Part 1 | The What?", url: "https://youtube.com/watch?v=z7IPBg6MyrU" },
        { title: "LSTM Architecture | Part 2 | The How?", url: "https://youtube.com/watch?v=Akv3poqqwI4" ,articleLink:"https://colah.github.io/posts/2015-08-Understanding-LSTMs/", articleTitle:"Understanding LSTM Networks",notes:"NOTE: This is a great article with visualizations to understand LSTMs" },
        { title: "Article", url:"https://archive.ph/WPlJW", notes:"NOTE: This is a great article to visualize RNNs, LSTM and GRUs architecture." },
        { title: "LSTM | Part 3 | Next Word Predictor Using LSTM", url: "https://youtube.com/watch?v=fiqo6uPCJVI" },
        { title: "Gated Recurrent Unit | Deep Learning | GRU", url: "https://youtube.com/watch?v=QQfZAoNGQmE" },
        { title: "Deep RNNs | Stacked RNNs | Stacked LSTMs | Stacked GRUs", url: "https://youtube.com/watch?v=mlDkTrlLaio" },
        { title: "Bidirectional RNN | BiLSTM | Bidirectional GRU", url: "https://youtube.com/watch?v=k2NSm3MNdYg" }
    ],
    "Encoder-Decoder Architecture": [
        { title: "Encoder Decoder | Sequence-to-Sequence Architecture", url: "https://youtube.com/watch?v=KiL74WsgxoA",articleLink:"https://medium.com/analytics-vidhya/encoder-decoder-seq2seq-models-clearly-explained-c34186fbf49b",articleTitle:"Encoder-Decoder (Seq2Seq) Models Clearly Explained",notes:"NOTE: This is a great article to understand the Encoder-Decoder architecture." },
        { title: "RESEARCH PAPER", url:"https://arxiv.org/pdf/1409.3215", notes:"NOTE: This is the original paper on Seq2Seq Networks. A must read." },
        { title: "Attention Mechanism in 1 video | Seq2Seq Networks", url: "https://youtube.com/watch?v=rj5V6q6-XUM" ,articleLink:"https://towardsdatascience.com/intuitive-understanding-of-attention-mechanism-in-deep-learning-6c9482aecf4f",articleTitle:"Intuitive Understanding of Attention Mechanism in Deep Learning"},
        { title: "Bahdanau Attention Vs Luong Attention", url: "https://youtube.com/watch?v=0hZT4_fHfNQ" , articleLink:"https://medium.com/data-science-community-srm/understanding-encoders-decoders-with-attention-based-mechanism-c1eb7164c581",articleTitle:"Understanding Encoders & Decoders with Attention Based Mechanism"},
        { title: "PROJECT WORK", url:"https://towardsdatascience.com/text-summarization-from-scratch-using-encoder-decoder-network-with-attention-in-keras-5fa80d12710e", notes:"This is a good project to implement the Encoder-Decoder architecture."},
        { title: "PROJECT WORK", url:"https://github.com/anshaneja5/img-cap-model", notes:"This is a Image Captioning project to implement the Encoder-Decoder architecture. It uses DenseNet and LSTMs. Do check it out and try to implement it yourself."}
    ],
    "Natural Language Processing": [
        { title: "Introduction to NLP | NLP Lecture 1 | End to End NLP Course", url: "https://youtube.com/watch?v=zlUpTlaxAKI" },
        { title: "End to End NLP Pipeline | NLP Pipeline | Lecture 2 NLP Course", url: "https://youtube.com/watch?v=29qyNyNkLHs" },
        { title: "Text Preprocessing | NLP Course Lecture 3", url: "https://youtube.com/watch?v=6C0sLtw5ctc" },
        { title: "Text Representation | NLP Lecture 4 | Bag of Words | Tf-Idf | N-grams, Bi-grams and Uni-grams", url: "https://youtube.com/watch?v=vo6gQz5lYRI" },
        { title: "Word2vec Complete Tutorial | CBOW and Skip-gram | Game of Thrones Word2vec", url: "https://youtube.com/watch?v=DDfLc5AHoJI" , articleLink:"https://jalammar.github.io/illustrated-word2vec/", articleTitle:"The Illustrated Word2Vec"},
        { title: "VISUALIZATION", url:"https://projector.tensorflow.org/", notes:"This is a great tool to visualize word embeddings."},
        { title: "Text Classification | NLP Lecture 6 | End to End | Average Word2Vec", url: "https://youtube.com/watch?v=Qbd7U9F0QQ8" },
        { title: "POS Tagging | Part of Speech Tagging in NLP | Hidden Markov Models in NLP | Viterbi Algorithm in NLP", url: "https://youtube.com/watch?v=269IGagoJfs" },
        { title: "Duplicate Question Pairs | Quora Question Pairs | NLP Projects | End to End NLP Project | Heroku", url: "https://youtube.com/watch?v=1fvQU5yPjFs" , articleLink:"https://github.com/anshaneja5/quora-question-pairs", articleTitle:"Quora Question Pairs Github Repo"},
        { title: "KAGGLE COMPETITION", url:"https://www.kaggle.com/competitions/nlp-getting-started/overview", notes:"This is a good competition to participate in to implement all the above topics."}
    ],
    "Transformers": [
        { title: "Introduction to Transformers | Transformers Part 1", url: "https://youtube.com/watch?v=BjRVS2wTtcA",articleLink:"https://arxiv.org/pdf/1706.03762",articleTitle:"Attention is All You Need (RESEARCH PAPER)",notes:"NOTE: This is the original paper on Transformers." },
        { title: "What is Self Attention | Transformers Part 2", url: "https://youtube.com/watch?v=XnGGmvpDLA0" },
        { title: "Self Attention in Transformers | Simple Explanation with Code!", url: "https://youtube.com/watch?v=-tCKPl_8Xb8" },
        { title: "Scaled Dot Product Attention | Why do we scale Self Attention?", url: "https://youtube.com/watch?v=r7mAt0iVqwo" },
        { title: "Self Attention Geometric Intuition | How to Visualize Self Attention | CampusX", url: "https://youtube.com/watch?v=5ZgGuujZSbs" },
        { title: "Why is Self Attention called 'Self'? | Self Attention Vs Luong Attention in Depth Lecture | CampusX", url: "https://youtube.com/watch?v=o4ZVA0TuDRg" },
        { title: "What is Multi-head Attention in Transformers", url: "https://youtube.com/watch?v=bX2QwpjsmuA" },
        { title: "Positional Encoding in Transformers", url: "https://youtube.com/watch?v=GeoQBNNqIbM" },
        { title: "Layer Normalization in Transformers | Layer Norm Vs Batch Norm", url: "https://youtube.com/watch?v=qti0QPdaelg" },
        { title: "Transformer Architecture | Part 1 Encoder Architecture", url: "https://youtube.com/watch?v=Vs87qcdm8l0" },
        { title: "Masked Self Attention | Masked Multi-head Attention in Transformer", url: "https://youtube.com/watch?v=m6onaKFzF94" },
        { title: "Cross Attention in Transformers" , url: ",https://youtube.com/watch?v=smOnJtCevoU"}, 
        { title: "Transformer Decoder Architecture" , url: "https://youtube.com/watch?v=DI2_hrAulYo"}, 
        { title: "Transformer Inference | How Inference is done in Transformer?", url: "https://youtube.com/watch?v=FtsMOzlwxws",articleLink:"https://jalammar.github.io/illustrated-transformer/",articleTitle:"The Illustrated Transformer",notes:"NOTE: This is a great article to understand the transformer architecture."},
    ]
};

export default categorizedDLVideos;