An AI engineer guide to Machine Learning with Keras

If you would like to go deep into Keras to perform the deep learning, this tutorial is for you. The GitHub url is there to get the notebooks for this video and code is ready to try locally or at Google colab. Please check out the content timeline jump to specific chapter as well:

Video Content with Timeline:

(00:00) video start (00:07) Content intro

(03:35) Google Colab and notebook Intro (05:26) 1st Notebook (model with only training data) (05:59) Data Import (08:28) EDA (Exploratory Data Analysis) (12:40) Data Split (Train and Target) (14:24) Training data Transformation (16:00) Train and Test Data Split (16:34) Setup model network and layers (18:02) Network Visualization (19:12) Callback function to plot loss per epoch (20:26) Compile Model (22:00) Start Model Training (23:27) Callback function to plot loss & accuracy per epoch (24:36) Check model loss and accuracy in real time (25:31) Validate Model History (26:20) Check Model Performance (27:17) 2nd Notebook (model with training & validation data) (29:40) Training data split into Train & Validation data (31:02) Compile Model & start Model Training (31:33) Check model loss and accuracy with validation in real time (33:01) Check Model Performance (33:43) Saving colab notebook to Github (34:42) Credits

GitHub URL https://github.com/prodramp/publiccode/tree/master/machine_learning/keras-heart-disease-live-epochs

Please visit: https://prodramp.com | @prodramp https://www.linkedin.com/company/prodramp

Content Creator: Avkash Chauhan (@avkashchauhan) https://www.linkedin.com/in/avkashchauhan

Tags: #webdevelopment, #frontend #react #chakraui #fullstack #uidevelopment #uicomponents #redux #react-redux #JavaScript #python #googlecolab #github #access #appdev #devops #GitHub #cmdline #gitclone #machinelearning #deeplearning #keras #model #modelhistory #modelperformance #prodramp #avkash #heartdisease ... https://www.youtube.com/watch?v=sH-J3SeEpGs