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Download Machine Learning Course ( Coding Ninjas ) Free Download – Google Drive Links

Download Machine Learning Course ( Coding Ninjas ) Free Download – Google Drive Links

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Download Machine Learning Course ( Coding Ninjas ) Free Download - Google Drive Links 2

Projects that you will get going..

Tendency Descent Implementation

Execute the standard Gradient Descent computation for headway of a model (Regression or Neural)

Vital Regression Implementation

Execute the standard Logistic Regression model usually used for orchestrating data into twofold classes like pass/misfire, win/lose, alive/dead or sound/crippled.

Decision Tree Implementation

Execute the standard Decision Tree Class used for describing data into various classes using a tree-like model of decisions and their expected outcomes.

Picture Caption Generation

Gather a CNN/LSTM based model to give a caption to the given picture.

Involved Driver Detection

Manufacture a plan model to anticipate using a data base of pictures whether a given driver is redirected, ie, informing, on a call, driving safely, etc

Text Generation

Collect a Neural Network based model to predict what the accompanying word will be in a gathering of words/sentences

Brain Machine Translation

Develop a general model with the ultimate objective of translation of articulations and pictures starting with one language then onto the next using Artificial Neural Network.

Metropolitan Sound Classification

Gather a Neural association based model to portray various sounds using their uncommon spectrogram into classes like Dog Barking, Sirens, Street Music, etc

Text Classification

Gather a classifier model using Naive Bayes estimation to expect the subject of an article present in a paper

Picture Classification (CIFAR-10 Dataset)

Integrate a classifier for describing 10,000 pictures into 10 classes (canine, pony, cat, etc) using the CIFAR-10 Dataset.

Twitter Sentiment Analysis

Separate the tweets introduced on twitter on expect the assessment of the tweet for instance certain, negative or fair-minded

Facial Emotion Recognition

Build a general model with the ability to expect the facial sensation of a person in an image.

Develop Facial Emotion Recognition, Distracted Driver Detection activities and astonish determination delegates to get extraordinary positions


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