Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial
Why Stack Overflow recommends it
Stack Overflow users who are beginners learning Keras follow this tutorial step by step, then post questions when their model's predictions or accuracy don't match what the video shows.
Recommended by 0 people across 0 different months, 2021 to 2022.
What it is
A 2h47m freeCodeCamp course by deeplizard that teaches Keras with TensorFlow from scratch. It covers data preprocessing, building and training dense networks, validation sets, predictions, confusion matrices, saving models, CNNs, fine-tuning and transfer learning.
What people said
Cites Colby Ryan Freeman · 2021-01 · Stack Overflow · on “Neural network predictions not as expected”
I'm following a youtube video tutorial on neural networks, using Keras. The training data is randomly generated. It's some made-up clinical trial. The goal of the neural network is to predict the probability of someone having side effects, or not. Here is the video: [this video] Here are the results of the prediction, from the video: [LINK] Here are the results from one of my predictions: [LINK] If the second number is 1, or close to 1, that means it is probable they will have side effects. It seems like no matter what data I put into the testing array, the second output is going to always be 1. I don't know what I'm doing wrong. My code is organized a little differently, and I don't generate a t
Cites MsTais · 2021-03 · Stack Overflow · on “Keras, simple CNN with binary classification doesn't converge — minimal example (from DeepLizard)”
I am new to NN and Keras. I have tried this tutorial [this video] from DeepLizard and followed it until the lady showed the first training results ~30min in. I followed the steps exactly except the lines with 'shuffle' since that was not how it is supposed to be used (to my knowledge). Here is my code: import numpy as np import random as random from random import randint from sklearn.preprocessing import MinMaxScaler from random import shuffle train_labels = [] train_samples = [] for i in range(50): random_younger = randint(13,64) train_samples.append(random_younger) train_labels.append(1) random_older = randint(65,100) train_samples.append(random_older) train_labels.append(0) for i in range (100
Cites Feen · 2022-04 · Stack Overflow · on “TensorFlow Keras issues”
I'm trying to learn the very basics of Keras and how to use it and I'm running into trouble getting my model to work. I am following a tutorial online ( [this video] ) word for word and getting errors when using the model.fit() function this is the second tutorial I have tried and gotten the same result. I have looked at Keras's website and read all of the variable descriptions for the functions/followed instructions on site, and cannot work around the issue. I am running this in a virtual environment with TensorFlow 2.0.0 and Keras 2.3.1 It may be worth noting that I am on an M1 MacBook Pro (not sure if that's the issue). This is my first experience with Python and machine learning. Code: CodeIm
Cites Gianluca · 2022-07 · Stack Overflow · on “Accuracy fixed at 50% keras”
I am new to tensorflow and keras, I am trying to follow a tutorial on keras ( [this video] min.38:40) and everything seems to work but as soon as I run the fit, accuracy remains almost fixed at 50% and I can't understand why, can someone help me? Here is the code: import tensorflow as tf from tensorflow import keras from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Activation, Dense from tensorflow.keras.optimizers import Adam from tensorflow.keras.metrics import categorical_crossentropy import numpy as np from random import randint from sklearn.utils import shuffle from sklearn.preprocessing import MinMaxScaler train_labels = [] train_samples = [] for i in range(