In this lecture, we will study analysis of Time series data. Step -01: Read data and make sure that you convert date column datatype to DateTime object. data = pd.read_csv('airline-passenger-traffic.csv', header = None) data.columns = ['Month','Passengers'] data['Month'] = pd.to_datetime(data['Month'], format='%Y-%m') data = data.set_index('Month') data.head(12) Step-02: Plot Time Series data data.plot(figsize=(12…

In this lecture, we will study Application, Types, Basic Terminology, Basic Approach and three Principles of forecasting. Application of Forecasting Economic Outlook → Government use Sales Forecasting → how many products goes to sell (Sales figure) and decide production amount in factory Inventory Planning → How much to stock in…

Objective of writing: Preparing Notes or my learnings from course — Statistics Foundations: The Basics. Don’t have any intention to spam. Mean, Median and Mode Mean → Average

In our previous Lecture 01, we studied about Matrix Operations (Initialization, Vector, Multiplication, Transpose, Special Matrix) https://medium.com/math-for-data-science/math-for-data-science-bits-wilp-program-58417c654665 In this lecture, we will study Elementary row operations to find solution of linear equations. …

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In this lecture, we will study Matrix Operations (Initialization, Vector, Multiplication, Transpose, Special Matrix) via Python. Matrix Definition Matrix Notation

Objectives → By end of this, you will be able to use Various Pre-trained NLP Models from TensorFlow Hub (thub.dev) Use transfer learning to fine tune text data Visualize Model Performance metric with Tensorboard Problem Statement → Detect Toxic Comment (Quora Insincere Questions Classification) !nvidia-smi → Command to tell GPU status

Different Types of RNN

In Language Model, we find probability of sentence. Decoder in Machine Translation system is same as Language Model and a<0> in language model is similar to Encoder in Machine Translation. In M/C Translation, we use beam search instead of greedy search.