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Implementation of Linear/Logistic Reg, K-NN, SVM, Clustering, K-Means, ConvNet, ResNet, MobileNet, RNN, LSTM etc. using Pandas, SciKitLearn, NumPy & TensorFlow 2

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RNN_Application
RNN_Application
 
 
Recommendation_Systems
Recommendation_Systems
 
 
__pycache__
__pycache__
 
 
emojifier
emojifier
 
 
pygame
pygame
 
 
word2vec
word2vec
 
 
.DS_Store
.DS_Store
 
 
.gitignore
.gitignore
 
 
Initialization Regularization.ipynb
Initialization Regularization.ipynb
 
 
Kmeans_image_compression.ipynb
Kmeans_image_compression.ipynb
 
 
L Layer Neural Net.ipynb
L Layer Neural Net.ipynb
 
 
Mean-Shift-From-Scratch.py
Mean-Shift-From-Scratch.py
 
 
Mean-Shift-Titanic.py
Mean-Shift-Titanic.py
 
 
MobileNet.ipynb
MobileNet.ipynb
 
 
README.md
README.md
 
 
Self_made_model.ipynb
Self_made_model.ipynb
 
 
anomaly_detection.ipynb
anomaly_detection.ipynb
 
 
conv_tensorflow_practice.ipynb
conv_tensorflow_practice.ipynb
 
 
convnet_pytorch.ipynb
convnet_pytorch.ipynb
 
 
convolution-practice-tensorflow.ipynb
convolution-practice-tensorflow.ipynb
 
 
convolution-practice.ipynb
convolution-practice.ipynb
 
 
cuda-keyring_1.1-1_all.deb
cuda-keyring_1.1-1_all.deb
 
 
deep-net.py
deep-net.py
 
 
helper_functions.py
helper_functions.py
 
 
kmeans-titanic-clustering.py
kmeans-titanic-clustering.py
 
 
kmeans.py
kmeans.py
 
 
linear-regression-tf2.py
linear-regression-tf2.py
 
 
mean-shift-sklearn.py
mean-shift-sklearn.py
 
 
melbourne.py
melbourne.py
 
 
meta_llama3_inference.py
meta_llama3_inference.py
 
 
mnist-tensorflow2.py
mnist-tensorflow2.py
 
 
model.log
model.log
 
 
multiclass_classification.ipynb
multiclass_classification.ipynb
 
 
multiclass_classification_pytorch.ipynb
multiclass_classification_pytorch.ipynb
 
 
phi3_inference.py
phi3_inference.py
 
 
random_mini_batch_with_adam.py
random_mini_batch_with_adam.py
 
 
resnet.ipynb
resnet.ipynb
 
 
rnn_practice.ipynb
rnn_practice.ipynb
 
 
svm.py
svm.py
 
 
tensorflow-basic.py
tensorflow-basic.py
 
 
tensorflow-fashion-mnist.ipynb
tensorflow-fashion-mnist.ipynb
 
 
transfer_learning_part_1.ipynb
transfer_learning_part_1.ipynb
 
 
transfer_learning_part_2.ipynb
transfer_learning_part_2.ipynb
 
 
utility-functions.py
utility-functions.py
 
 

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Machine-Leanring-Deep-Dive

Implementation of Linear Reg., K-NN, SVM, Kernal, RNN, ConvNet & 3D ConvNet using SciKitLearn, NumPy, Matpoltlib & TensorFlow

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Implementation of Linear/Logistic Reg, K-NN, SVM, Clustering, K-Means, ConvNet, ResNet, MobileNet, RNN, LSTM etc. using Pandas, SciKitLearn, NumPy & TensorFlow 2

shubhamswe.xyz

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scikit-learn matplotlib convolutional-neural-networks tensorflow2

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