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Welcome to Just into Data, a place for data science made simpleR!
Enjoy data science articles on various topics such as Machine Learning, AI, Statistical Modeling, Python Programming.
How to do Sentiment Analysis with Deep Learning (LSTM Keras)
Automatically Classify Reviews as Positive or Negative in Python
In this tutorial, we build a deep learning neural network model to classify the sentiment of Yelp reviews.
Following the step-by-step procedures in Python, you’ll see a real life example and learn:
– How to prepare review text data for sentiment analysis, including NLP techniques.
– How to tune the hyperparameters for the machine learning models.
– How to predict sentiment by building an LSTM model in Tensorflow Keras.
– How to evaluate model performance.
– How sample sizes impact the results compared to a pre-trained tool.
And more.
3 Steps to Time Series Forecasting: LSTM with TensorFlow Keras
A Practical Example in Python with useful Tips
We present a deep learning time series analysis example with Python. You’ll see:
– How to preprocess/transform the dataset for time series forecasting.
– How to handle large time series datasets when we have limited computer memory.
– How to fit Long Short-Term Memory (LSTM) with TensorFlow Keras neural networks model.
Hyperparameter Tuning with Python: Keras Step-by-Step Guide
Why and How to use with an example of Keras
This is a practical guide to Hyperparameter Tuning in Python.
To improve your model’s performance, learn:
– why you should use this machine learning technique.
– how to use it with Keras and Tensorflow step-by-step with Python.
Hyperparameter Tuning with Python: Complete Step-by-Step Guide
Why and How to use with an example of XGBoost
This is a practical guide to Hyperparameter Tuning in Python.
To improve your model’s performance, learn:
– why you should use this machine learning technique.
– how to use it with XGBoost step-by-step with Python.
What is the Coronavirus Death Rate with Hyperparameter Tuning
Examine the death rate and time to death/recovery distribution with Python
We examine the death rate and time to death/recovery distribution of coronavirus with Python.
You’ll see the step-by-step procedures of how to find the parameters of a model that is best fitting the COVID-19 data.
If you want:
– more insights about coronavirus
– or to see an example of hyperparameter tuning/optimization in Python
take a look!
How to Install/Setup Python and Prep for Data Science NOW
Step-by-Step process to be ready for Data Science, Machine Learning, Deep Learning
We’ll walk you through the step-by-step process to set up the Python environment.
You’ll learn:
– How to install Python with Anaconda distribution.
– How to use Python through tools such as Jupyter Notebook.
– What are the Python packages that help with the end-to-end process (from analyzing data to deploying models).