[FEATURE REQUEST]: Implement ML Features

** These should all be implemented with https://github.com/dotnet/spark/pull/1031 **

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This is to track implementation of the ML-Features: https://spark.apache.org/docs/latest/ml-features

Bucketizer has been implemented in https://github.com/dotnet/spark/pull/378 but there are more features that should be implemented.

- [ ] Feature Extractors
- [x] TF-IDF
- [x] Word2Vec (https://github.com/dotnet/spark/pull/491)
- [x] CountVectorizer (https://github.com/dotnet/spark/pull/608)
- [x] FeatureHasher (https://github.com/dotnet/spark/pull/652)
- [ ] Feature Transformers
- [x] Tokenizer (https://github.com/dotnet/spark/pull/574)
- [x] StopWordsRemover (https://github.com/dotnet/spark/pull/726 thanks @SARAVANA1501 )
- [x] n-gram (in-progress #734)
- [x] Binarizer (in-progress #744)
- [] PCA (in-progress)
- [ ] PolynormalExpansion
- [ ] Dicrete Cosine Transform (DCT)
- [ ] StringIndexer (in-progress)
- [ ] IndexToString
- [ ] OneHotEncoderEstimator
- [ ] VectorIndexer
- [ ] Normalizer
- [ ] StandardScaler
- [ ] MinMaxScaler
- [ ] MaxAbsScaler
- [X] Bucketizer
- [ ] ElementwiseProduct
- [x] SQLTransformer (https://github.com/dotnet/spark/pull/781 @ramanathanv)
- [ ] VectorAssembler
- [ ] VectorSizeHint
- [ ] QuantileDiscretizer
- [ ] Imputer
- [ ] Feature Selectors
- [ ] VectorSlicer
- [ ] RFormula
- [ ] ChiSqSelector
- [ ] Locality Sensitive Hashing
- [ ] LSH Operations
- [ ] Feature Transformation
- [ ] Approximate Similarity Join
- [ ] Approximate Nearest Neighbour Search
- [ ] LSH Algorithms
- [ ] Bucketed Random Projection for Euclidean Distance
- [ ] MinHash for Jaccard Distance

If anyone else is going to implement probably best to put a comment here and I'll keep the list up to date.