bgalvao

# SSD with Mobilenet v2 configuration for OpenImages V4 Dataset.
# Users should configure the fine_tune_checkpoint field in the train config as
# well as the label_map_path and input_path fields in the train_input_reader and
# eval_input_reader. Search for "PATH_TO_BE_CONFIGURED" to find the fields that
# should be configured.

model {
  ssd {
    num_classes: 601
    box_coder {

bgalvao

#!/usr/bin/python
import numpy as np
import requests
from colored import fg, bg, attr

# after probing, I found out that these are the possible values
# [0, 140[
url = "https://indie-hackers.firebaseio.com/loadingQuotes/{}.json".format(
	np.random.choice(140)
)

bgalvao

# installed bazel in a new conda env

# git clone https://github.com/tensorflow/tensorflow --depth 1
# move this file into the repo clone
# touch WORKSPACE inside the clone

# if [ ! -d tensorflow ]; then
#     echo "tensorflow clone not yet here. cloning it..."
#     git clone https://github.com/tensorflow/tensorflow --depth 1
# fi

bgalvao

FROM continuumio/miniconda3

RUN conda install -c conda-forge -y pandas scipy
RUN conda install -c conda-forge -y matplotlib seaborn
RUN conda install -c conda-forge -y bowtie-py tqdm
RUN conda install -c conda-forge -y scikit-learn jupyterlab
RUN conda install -c conda-forge -y ipywidgets plotly dash
RUN jupyter labextension install @jupyterlab/plotly-extension
RUN jupyter labextension install @jupyter-widgets/jupyterlab-manager
RUN conda install -c conda-forge -y dask-ml dask-distance

bgalvao

Learning Checklist

Generic Neural Nets

• Convolutional Neural Networks
• Autoencoders
• Recurrent Neural Nets (LSTM)

Domains

• Symbiotic GP game playing agent with Autoencoder + RNN processing layer. #biggestscope
• CyberSec dataset from Stratosphere Lab.